- published: 07 Jun 2019
- views: 25521
Silhouette
A silhouette is the image of a person, animal, object or scene represented as a solid shape of a single color, usually black, its edges matching the outline of the subject. The interior of a silhouette is featureless, and the whole is typically presented on a light background, usually white, or none at all. The silhouette differs from an outline, which depicts the edge of an object in a linear form, while a silhouette appears as a solid shape. Silhouette images may be created in any visual artistic media, but was first used to describe pieces of cut paper, which were then stuck to a backing in a contrasting colour, and often framed.
Cutting portraits, generally in profile, from black card became popular in the mid-18th century, though the term silhouette was seldom used until the early decades of the 19th century, and the tradition has continued under this name into the 21st century. They represented a cheap but effective alternative to the portrait miniature, and skilled specialist artists could cut a high-quality bust portrait, by far the most common style, in a matter of minutes, working purely by eye. Other artists, especially from about 1790, drew an outline on paper, then painted it in, which could be equally quick. The leading 18th-century English "profilist" in painting, John Miers, advertised "three minute sittings", and the cost might be as low as half a crown around 1800. Miers' superior products could be in grisaille, with delicate highlights added in gold or yellow, and some examples might be painted on various backings, including gesso, glass or ivory. The size was normally small, with many designed to fit into a locket, but otherwise a bust some 3 to 5 inches high was typical, with half- or full-length portraits proportionately larger.
This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Silhouette
Deus Ex
Deus Ex is a cyberpunk-themed action role-playing video game—combining first-person shooter, stealth and role-playing elements—developed by Ion Storm and published by Eidos Interactive in 2000. First published for personal computers running Microsoft Windows, Deus Ex was later ported to Mac OS systems and PlayStation 2. Set in a dystopian world during the year 2052, the central plot follows rookie United Nations Anti-Terrorist Coalition agent JC Denton, as he sets out to combat terrorist forces, which have become increasingly prevalent in a world slipping ever further into chaos. As the plot unfolds, Denton becomes entangled in a deep and ancient conspiracy, encountering organizations such as Majestic 12, the Illuminati and the Hong Kong Triads during his journey.
The game received universal critical acclaim, including repeatedly being named "Best PC Game of All Time" in PC Gamer's "Top 100 PC Games" in 2011 and in a poll carried out by UK gaming magazine PC Zone. It was a frequent candidate for and winner of Game of the Year awards, drawing praise for its pioneering designs in player choice and multiple narrative paths. It has sold more than 1 million copies, as of April 23, 2009. The game has spawned both a sequel, Deus Ex: Invisible War, released in 2003, and a prequel, Deus Ex: Human Revolution, released in 2011.
This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Deus_Ex
Silhouette (clustering)
Silhouette refers to a method of interpretation and validation of consistency within clusters of data. The technique provides a succinct graphical representation of how well each object lies within its cluster. It was first described by Peter J. Rousseeuw in 1986.
Definition
Assume the data have been clustered via any technique, such as k-means, into 
clusters. For each datum 
, let 
be the average dissimilarity of with all other data within the same cluster. We can interpret as how well is assigned to its cluster (the smaller the value, the better the assignment). We then define the average dissimilarity of point to a cluster 
as the average of the distance from to all points in .
Let 
be the lowest average dissimilarity of to any other cluster, of which is not a member. The cluster with this lowest average dissimilarity is said to be the "neighbouring cluster" of because it is the next best fit cluster for point .
We now define a silhouette:
Which can be also written as:
This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Silhouette_(clustering)
Obsession (Sky Ferreira song)
"Obsession" is a song by American recording artist Sky Ferreira. The song was written by Justin "DJ Frank E" Franks with OneRepublic members Ryan Tedder and Jerrod Bettis, both of whom co-produced it with DJ Frank E. The song was released as a single on September 14, 2010 by Capitol Records. "Obsession" has been compared to "Rock and Roll" by Gary Glitter and "I Kissed a Girl" by Katy Perry. The song peaked at number thirty-seven on Billboard's Hot Dance Club Songs. The music video for the song was directed by Marc Klasfeld, and portrays Ferreira's obsession with actor Michael Madsen.
Background and composition
"Obsession" was written and produced by Ryan Tedder, Jerrod Bettis, and DJ Frank E. Ferreira said of the song:
Following its release, "Obsession" has been featured on Now That's What I Call Music! 35, the first soundtrack to The Vampire Diaries, and the soundtrack to the 2011 romantic comedy film Larry Crowne. A remix of the song by Static Revenger was also included on Now That's What I Call Club Hits 2.
This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Obsession_(Sky_Ferreira_song)
Obsession: Radical Islam's War Against the West
Obsession: Radical Islam's War Against the West is a 2005 documentary film about the perceived threat of radical Islam to Western civilization. The film makes use of extensive Arab television footage depicting Islamic radicals preaching hate speech and seeking to incite global jihad. It also draws parallels between World War II's Nazi movement and Islamism and the West's response to those threats.
Wayne Kopping of South Africa co-wrote and directed the film. Raphael Shore, a Canadian-Israeli, co-wrote and produced the film, and is the founder of The Clarion Fund, the film's distributor. The movie has received praise from conservative media personalities such as Glenn Beck and Sean Hannity, but others criticized it as Islamophobic with a political agenda, and for its association with pro-Israeli groups.
Segments of the movie were broadcast on CNN Headline News and in several specials on Fox News. The movie was also screened on 30 college campuses and Capitol Hill. The unusual distribution of 28 million free Obsession DVDs as an insert in over 70 newspapers predominantly in swing states before the United States 2008 presidential election, garnered much attention, with 5 newspapers refusing to distribute the DVD. National Public Radio reported that it was unclear as to who funded Clarion's distribution of the DVD.
This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Obsession:_Radical_Islam's_War_Against_the_West
Obsession (novel)
Obsession is a mystery novel by American author Jonathan Kellerman. It is the 21st novel in the Alex Delaware series.
Plot introduction
Tanya Bigelow, a former patient, comes to Alex requesting help. She wants him and his friend Milo to investigate something her mother said on her death bed. Her mother told her that she did something terrible. No one believes that Tanya's mother Patty, who worked with Milo's partner at the hospital as a nurse, could have done anything terrible, but as the reader learns her past, it contains dark secrets. Alex has a new dog, Blanche, that Robin bought him after Spike died. Robin is living with Alex again.
Characters in "Obsession"
This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Obsession_(novel)
Forever (Puff Daddy album)
Forever is the debut solo studio album (and second overall) by American rapper and producer Puff Daddy released on August 24, 1999 in North America by Bad Boy Records, with a release in the United Kingdom the following day.
Forever received generally favorable to mixed reviews from most music critics, directed at the heavy use of sampling in Combs' work, as well as commercially changing hip-hop music simultaneously, which caused controversy at the time. It debuted at number two on the Billboard 200 album chart. To date, the album has received positive to mixed reviews from music critics, and has spawned three singles that have attained Billboard chart success. In late 1999, Forever was later certified platinum by the Recording Industry Association of America (RIAA) for shipping over one million units in North America.
Background and production
The album comes nearly two years after Combs joint collaboration album, No Way Out, which opened on the US Billboard 200 at number one, and won the Grammy Award for Best Rap Album in February 1998, whereas Combs (under the name "Puff Daddy"), was nominated for Best New Artist, which he lost. He also collaborated with Jimmy Page of Led Zeppelin, for the single "Come with Me" for the 1998 film Godzilla. The song had sampled "Kashmir" by Led Zeppelin, and reached #2 on the UK Singles Chart, whilst stalling at #4 on the US Billboard Hot 100. He was also obligated to star as Willie Beamen in the motion picture, Any Given Sunday, the role however went to Jamie Foxx.
This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Forever_(Puff_Daddy_album)
Podcasts:
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0405 Number of Clusters as a Hyperparameter The Elbow and Silhouette Method
published: 07 Jun 2019 -
Silhouette Score for clustering Explained | Silhouette (clustering)- Validating Clustering Models
Silhouette Score for clustering Explained | Silhouette (clustering)- Validating Clustering Models #SilhouetteScore #UnfoldDataScience Hello , My name is Aman and I am a Data Scientist. About this video: In this video, I speak about Silhouette Score and explain step by step how Silhouette Score works for cluster validation. I explain how to validate clusters and how to measure goodness of clusters. I explain the mathematical formula of Silhouette Score and intuition behind it. Below points are discussed in this video: 1. Silhouette Score for clustering 2. Validation on K-means clusters 3. Cluster validation techniques 4. How to measure goodness of clusters 5. Unsupervised machine learning accuracy About Unfold Data science: This channel is to help people understand basics of data scienc...
published: 20 May 2021 -
Machine Learning | Silhouette Coefficient
Silhouette refers to a method of interpretation and validation of consistency within clusters of data. The technique provides a succinct graphical representation of how well each object has been classified. #MachineLearning #SilhouetteCoefficient Machine Learning 👉https://www.youtube.com/playlist?list=PLPN-43XehstOjGY6vM6nBpSggHoAv9hkR Artificial Intelligence 👉https://www.youtube.com/playlist?list=PLPN-43XehstNQttedytmmLPwzMCXahBRg Cloud Computing 👉https://www.youtube.com/playlist?list=PLPN-43XehstNd5WsXQ9y3GFXyagkX1PC3 Wireless Technology 👉https://www.youtube.com/playlist?list=PLPN-43XehstMhFEXiOgJwv2Ec3vOTWpSH Data Mining 👉https://www.youtube.com/playlist?list=PLPN-43XehstOe0CxcXaYeLTFpgD2IiluP Simulation Modeling 👉https://www.youtube.com/playlist?list=PLPN-43XehstPwUMDCs9zYQS-e5-0...
published: 16 Nov 2019 -
How to Compute Silhouette Coefficient – K Means Clustering in Machine Learning by Mahesh Huddar
How to Compute Silhouette Coefficient – K Means Clustering in Machine Learning by Mahesh Huddar The following concepts are discussed: ______________________________ How to Compute Silhouette Coefficient, K Means Clustering, Silhouette Coefficient in Machine Learning, Silhouette Coefficient in data mining, Silhouette Coefficient K Means Clustering ******************************** 1. Blog / Website: https://www.vtupulse.com/ 2. Like Facebook Page: https://www.facebook.com/VTUPulse 3. Follow us on Instagram: https://www.instagram.com/vtupulse/ 4. Like, Share, Subscribe, and Don't forget to press the bell ICON for regular updates
published: 22 Feb 2023 -
Silhouette (clustering)- Validating Clustering Models- Unsupervised Machine Learning
Reference Link: https://en.wikipedia.org/wiki/Silhouette_(clustering)#:~:text=The%20silhouette%20value%20is%20a,poorly%20matched%20to%20neighboring%20clusters. https://scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_analysis.html#sphx-glr-auto-examples-cluster-plot-kmeans-silhouette-analysis-py github: https://github.com/krishnaik06/Silhouette-clustering- Please donate if you want to support the channel through GPay UPID, Gpay: krishnaik06@okicici Discord Server Link: https://discord.gg/tvAJuuy Telegram link: https://t.me/joinchat/N77M7xRvYUd403DgfE4TWw Please join as a member in my channel to get additional benefits like materials in Data Science, live streaming for Members and many more https://www.youtube.com/channel/UCNU_lfiiWBdtULKOw6X0Dig/join Please do subs...
published: 25 Aug 2020 -
Silhouette Method for Right K || Lesson 108 || Machine Learning || Learning Monkey ||
#machinelearning#learningmonkey In this class, we discuss the silhouette method for right k. This is a measure of how well the give data point belongs to the cluster. After applying k means clustering we get different clusters. We take a data point and measure the mean distance of this data point to all other data points in the cluster. This gives how well this data point belongs to this cluster. In the same way, calculate the mean distance of the point to all other data points in the nearest cluster. This gives how dissimilar this data point belongs to other clusters. Now we define a silhouette value to the point. This value is between -1 and 1 Calculate all the data points and sum them. We pick the best k for which the value is higher. Link for playlists: https://www.youtube.com/ch...
published: 07 Sep 2020 -
Find the number of clusters in KMeans. Silhouette score. Python code example
Silhouette score is the metric that can find the optimal number of clusters in your data by using KMeans algorithm for clustering. Quick remind - Kmeans is an unsupervised learning in the area of Machine learning. With this video I explain and demonstrate how Silhouette score and curve works in real data. If you are working with clustering algorithms, probably you know the situation when you are not sure how many cluster to use is the best for your data science project if using classical Elbow method. Silhouette score is a good replacement for this. The silhouette value is a measure of how similar an object is to its own cluster (cohesion) compared to other clusters (separation). The silhouette ranges from −1 to +1, where a high value indicates that the object is well matched to its own ...
published: 23 Apr 2020 -
silhouette score for kmeans clustering
In our clustering analysis we use the Silhouette Score and typically comparing them across various numbers of clusters to help understand which works the best. Here we will use the yellowbrick library. This is meant to be a showcase of how I approach data science. If you're interested in learning more visit my profile to reserve a class now. Send me a message to get a copy of my full syllabus for my programs: basic python, data analyst, data science. Get a discount on your first class with this link. https://preply.com/en/?pref=NDU3ODY5OQ== Access the workbook here. https://github.com/brandynewanek/guided_projects/blob/main/KaggleYouTube_project1_Pokemon.ipynb
published: 11 Mar 2022 -
R- studio - K means clustering Using GAP ,Elbow and Silhouette method part 2
published: 11 May 2021
developed with YouTube
8:12
0405 Number of Clusters as a Hyperparameter The Elbow and Silhouette Method
- Order: Reorder
- Duration: 8:12
- Uploaded Date: 07 Jun 2019
- views: 25521
9:18
Silhouette Score for clustering Explained | Silhouette (clustering)- Validating Clustering Models
- Order: Reorder
- Duration: 9:18
- Uploaded Date: 20 May 2021
- views: 47821
Silhouette Score for clustering Explained | Silhouette (clustering)- Validating Clustering Models
#SilhouetteScore #UnfoldDataScience
Hello ,
My name is Aman a...
Silhouette Score for clustering Explained | Silhouette (clustering)- Validating Clustering Models
#SilhouetteScore #UnfoldDataScience
Hello ,
My name is Aman and I am a Data Scientist.
About this video:
In this video, I speak about Silhouette Score and explain step by step how Silhouette Score works for cluster validation. I explain how to validate clusters and how to measure goodness of clusters. I explain the mathematical formula of Silhouette Score and intuition behind it. Below points are discussed in this video:
1. Silhouette Score for clustering
2. Validation on K-means clusters
3. Cluster validation techniques
4. How to measure goodness of clusters
5. Unsupervised machine learning accuracy
About Unfold Data science: This channel is to help people understand basics of data science through simple examples in easy way. Anybody without having prior knowledge of computer programming or statistics or machine learning and artificial intelligence can get an understanding of data science at high level through this channel. The videos uploaded will not be very technical in nature and hence it can be easily grasped by viewers from different background as well.
If you need Data Science training from scratch . Please fill this form (Please Note: Training is chargeable)
https://docs.google.com/forms/d/1AcuamjqcAbVkWLN_RWdLMZbLYSGSfWMlJ8wn1VOpp3A/edit
Book recommendation for Data Science:
Category 1 - Must Read For Every Data Scientist:
The Elements of Statistical Learning by Trevor Hastie - https://amzn.to/37wMo9H
Python Data Science Handbook - https://amzn.to/31UCScm
Business Statistics By Ken Black - https://amzn.to/2LObAA5
Hands-On Machine Learning with Scikit Learn, Keras, and TensorFlow by Aurelien Geron - https://amzn.to/3gV8sO9
Ctaegory 2 - Overall Data Science:
The Art of Data Science By Roger D. Peng - https://amzn.to/2KD75aD
Predictive Analytics By By Eric Siegel - https://amzn.to/3nsQftV
Data Science for Business By Foster Provost - https://amzn.to/3ajN8QZ
Category 3 - Statistics and Mathematics:
Naked Statistics By Charles Wheelan - https://amzn.to/3gXLdmp
Practical Statistics for Data Scientist By Peter Bruce - https://amzn.to/37wL9Y5
Category 4 - Machine Learning:
Introduction to machine learning by Andreas C Muller - https://amzn.to/3oZ3X7T
The Hundred Page Machine Learning Book by Andriy Burkov - https://amzn.to/3pdqCxJ
Category 5 - Programming:
The Pragmatic Programmer by David Thomas - https://amzn.to/2WqWXVj
Clean Code by Robert C. Martin - https://amzn.to/3oYOdlt
My Studio Setup:
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Watch Introduction to Data Science full playlist here : https://www.youtube.com/watch?v=Zkyog5u1OGw&list=PLmPJQXJiMoUWXbjyedFTmXPzzoeMJV4fe
Watch python for data science playlist here:
https://www.youtube.com/watch?v=NTZkMI5tuh8&list=PLmPJQXJiMoUWtuekopnh4BhTFkDBvmhnC
Watch statistics and mathematics playlist here :
https://www.youtube.com/watch?v=iZ2r7aIwMbc&list=PLmPJQXJiMoUU52xCfjyoGRfoLCHKFtDxX
Watch End to End Implementation of a simple machine learning model in Python here:
https://www.youtube.com/watch?v=8PFt4Jin7B0&list=PLmPJQXJiMoUWKj26qv_Pw5Aofxncu84JB
Learn Ensemble Model, Bagging and Boosting here:
https://www.youtube.com/watch?v=fuO6QXAo-5M&list=PLmPJQXJiMoUWfMvIqAn0VI_LHlw4AmVrb
Build Career in Data Science Playlist:
https://www.youtube.com/watch?v=9pytkbvF8AU&list=PLmPJQXJiMoUWoG8fRUXPRcZec9LgdHmCL
Artificial Neural Network and Deep Learning Playlist:
https://www.youtube.com/watch?v=2-Cg_1FtHk8&list=PLmPJQXJiMoUVvvzXCBKSt0aA8A5NlryjV
Natural langugae Processing playlist:
https://www.youtube.com/watch?v=cs049uQWbpg&list=PLmPJQXJiMoUUSqSV7jcqGiiypGmQ_ogtb
Understanding and building recommendation system:
https://www.youtube.com/watch?v=juqpTaieIkA&list=PLmPJQXJiMoUWZeVfB5fle6dwyySg7xLMq
Access all my codes here:
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https://wn.com/Silhouette_Score_For_Clustering_Explained_|_Silhouette_(Clustering)_Validating_Clustering_Models
Silhouette Score for clustering Explained | Silhouette (clustering)- Validating Clustering Models
#SilhouetteScore #UnfoldDataScience
Hello ,
My name is Aman and I am a Data Scientist.
About this video:
In this video, I speak about Silhouette Score and explain step by step how Silhouette Score works for cluster validation. I explain how to validate clusters and how to measure goodness of clusters. I explain the mathematical formula of Silhouette Score and intuition behind it. Below points are discussed in this video:
1. Silhouette Score for clustering
2. Validation on K-means clusters
3. Cluster validation techniques
4. How to measure goodness of clusters
5. Unsupervised machine learning accuracy
About Unfold Data science: This channel is to help people understand basics of data science through simple examples in easy way. Anybody without having prior knowledge of computer programming or statistics or machine learning and artificial intelligence can get an understanding of data science at high level through this channel. The videos uploaded will not be very technical in nature and hence it can be easily grasped by viewers from different background as well.
If you need Data Science training from scratch . Please fill this form (Please Note: Training is chargeable)
https://docs.google.com/forms/d/1AcuamjqcAbVkWLN_RWdLMZbLYSGSfWMlJ8wn1VOpp3A/edit
Book recommendation for Data Science:
Category 1 - Must Read For Every Data Scientist:
The Elements of Statistical Learning by Trevor Hastie - https://amzn.to/37wMo9H
Python Data Science Handbook - https://amzn.to/31UCScm
Business Statistics By Ken Black - https://amzn.to/2LObAA5
Hands-On Machine Learning with Scikit Learn, Keras, and TensorFlow by Aurelien Geron - https://amzn.to/3gV8sO9
Ctaegory 2 - Overall Data Science:
The Art of Data Science By Roger D. Peng - https://amzn.to/2KD75aD
Predictive Analytics By By Eric Siegel - https://amzn.to/3nsQftV
Data Science for Business By Foster Provost - https://amzn.to/3ajN8QZ
Category 3 - Statistics and Mathematics:
Naked Statistics By Charles Wheelan - https://amzn.to/3gXLdmp
Practical Statistics for Data Scientist By Peter Bruce - https://amzn.to/37wL9Y5
Category 4 - Machine Learning:
Introduction to machine learning by Andreas C Muller - https://amzn.to/3oZ3X7T
The Hundred Page Machine Learning Book by Andriy Burkov - https://amzn.to/3pdqCxJ
Category 5 - Programming:
The Pragmatic Programmer by David Thomas - https://amzn.to/2WqWXVj
Clean Code by Robert C. Martin - https://amzn.to/3oYOdlt
My Studio Setup:
My Camera : https://amzn.to/3mwXI9I
My Mic : https://amzn.to/34phfD0
My Tripod : https://amzn.to/3r4HeJA
My Ring Light : https://amzn.to/3gZz00F
Join Facebook group :
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Watch Introduction to Data Science full playlist here : https://www.youtube.com/watch?v=Zkyog5u1OGw&list=PLmPJQXJiMoUWXbjyedFTmXPzzoeMJV4fe
Watch python for data science playlist here:
https://www.youtube.com/watch?v=NTZkMI5tuh8&list=PLmPJQXJiMoUWtuekopnh4BhTFkDBvmhnC
Watch statistics and mathematics playlist here :
https://www.youtube.com/watch?v=iZ2r7aIwMbc&list=PLmPJQXJiMoUU52xCfjyoGRfoLCHKFtDxX
Watch End to End Implementation of a simple machine learning model in Python here:
https://www.youtube.com/watch?v=8PFt4Jin7B0&list=PLmPJQXJiMoUWKj26qv_Pw5Aofxncu84JB
Learn Ensemble Model, Bagging and Boosting here:
https://www.youtube.com/watch?v=fuO6QXAo-5M&list=PLmPJQXJiMoUWfMvIqAn0VI_LHlw4AmVrb
Build Career in Data Science Playlist:
https://www.youtube.com/watch?v=9pytkbvF8AU&list=PLmPJQXJiMoUWoG8fRUXPRcZec9LgdHmCL
Artificial Neural Network and Deep Learning Playlist:
https://www.youtube.com/watch?v=2-Cg_1FtHk8&list=PLmPJQXJiMoUVvvzXCBKSt0aA8A5NlryjV
Natural langugae Processing playlist:
https://www.youtube.com/watch?v=cs049uQWbpg&list=PLmPJQXJiMoUUSqSV7jcqGiiypGmQ_ogtb
Understanding and building recommendation system:
https://www.youtube.com/watch?v=juqpTaieIkA&list=PLmPJQXJiMoUWZeVfB5fle6dwyySg7xLMq
Access all my codes here:
https://drive.google.com/drive/folders/1XdPbyAc9iWml0fPPNX91Yq3BRwkZAG2M
Have a different question for me? Ask me here : https://docs.google.com/forms/d/1ccglokA_FicF3AirR-xllXauKZrzmngJoUptza1tPRE/edit
My Music: https://www.bensound.com/royalty-free-music
- published: 20 May 2021
- views: 47821
7:09
Machine Learning | Silhouette Coefficient
- Order: Reorder
- Duration: 7:09
- Uploaded Date: 16 Nov 2019
- views: 24961
Silhouette refers to a method of interpretation and validation of consistency within clusters of data. The technique provides a succinct graphical representatio...
Silhouette refers to a method of interpretation and validation of consistency within clusters of data. The technique provides a succinct graphical representation of how well each object has been classified. #MachineLearning #SilhouetteCoefficient
Machine Learning 👉https://www.youtube.com/playlist?list=PLPN-43XehstOjGY6vM6nBpSggHoAv9hkR
Artificial Intelligence 👉https://www.youtube.com/playlist?list=PLPN-43XehstNQttedytmmLPwzMCXahBRg
Cloud Computing 👉https://www.youtube.com/playlist?list=PLPN-43XehstNd5WsXQ9y3GFXyagkX1PC3
Wireless Technology 👉https://www.youtube.com/playlist?list=PLPN-43XehstMhFEXiOgJwv2Ec3vOTWpSH
Data Mining 👉https://www.youtube.com/playlist?list=PLPN-43XehstOe0CxcXaYeLTFpgD2IiluP
Simulation Modeling 👉https://www.youtube.com/playlist?list=PLPN-43XehstPwUMDCs9zYQS-e5-0zjifX
Big Data 👉https://www.youtube.com/playlist?list=PLPN-43XehstPr1D-t9X2klE--Uj4YSNwn
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https://wn.com/Machine_Learning_|_Silhouette_Coefficient
Silhouette refers to a method of interpretation and validation of consistency within clusters of data. The technique provides a succinct graphical representation of how well each object has been classified. #MachineLearning #SilhouetteCoefficient
Machine Learning 👉https://www.youtube.com/playlist?list=PLPN-43XehstOjGY6vM6nBpSggHoAv9hkR
Artificial Intelligence 👉https://www.youtube.com/playlist?list=PLPN-43XehstNQttedytmmLPwzMCXahBRg
Cloud Computing 👉https://www.youtube.com/playlist?list=PLPN-43XehstNd5WsXQ9y3GFXyagkX1PC3
Wireless Technology 👉https://www.youtube.com/playlist?list=PLPN-43XehstMhFEXiOgJwv2Ec3vOTWpSH
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Simulation Modeling 👉https://www.youtube.com/playlist?list=PLPN-43XehstPwUMDCs9zYQS-e5-0zjifX
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- published: 16 Nov 2019
- views: 24961
6:02
How to Compute Silhouette Coefficient – K Means Clustering in Machine Learning by Mahesh Huddar
- Order: Reorder
- Duration: 6:02
- Uploaded Date: 22 Feb 2023
- views: 8341
How to Compute Silhouette Coefficient – K Means Clustering in Machine Learning by Mahesh Huddar
The following concepts are discussed:
_________________________...
How to Compute Silhouette Coefficient – K Means Clustering in Machine Learning by Mahesh Huddar
The following concepts are discussed:
______________________________
How to Compute Silhouette Coefficient,
K Means Clustering,
Silhouette Coefficient in Machine Learning,
Silhouette Coefficient in data mining,
Silhouette Coefficient K Means Clustering
********************************
1. Blog / Website: https://www.vtupulse.com/
2. Like Facebook Page: https://www.facebook.com/VTUPulse
3. Follow us on Instagram: https://www.instagram.com/vtupulse/
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https://wn.com/How_To_Compute_Silhouette_Coefficient_–_K_Means_Clustering_In_Machine_Learning_By_Mahesh_Huddar
How to Compute Silhouette Coefficient – K Means Clustering in Machine Learning by Mahesh Huddar
The following concepts are discussed:
______________________________
How to Compute Silhouette Coefficient,
K Means Clustering,
Silhouette Coefficient in Machine Learning,
Silhouette Coefficient in data mining,
Silhouette Coefficient K Means Clustering
********************************
1. Blog / Website: https://www.vtupulse.com/
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- published: 22 Feb 2023
- views: 8341
20:07
Silhouette (clustering)- Validating Clustering Models- Unsupervised Machine Learning
- Order: Reorder
- Duration: 20:07
- Uploaded Date: 25 Aug 2020
- views: 48550
Reference Link: https://en.wikipedia.org/wiki/Silhouette_(clustering)#:~:text=The%20silhouette%20value%20is%20a,poorly%20matched%20to%20neighboring%20clusters.
...
Reference Link: https://en.wikipedia.org/wiki/Silhouette_(clustering)#:~:text=The%20silhouette%20value%20is%20a,poorly%20matched%20to%20neighboring%20clusters.
https://scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_analysis.html#sphx-glr-auto-examples-cluster-plot-kmeans-silhouette-analysis-py
github: https://github.com/krishnaik06/Silhouette-clustering-
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https://wn.com/Silhouette_(Clustering)_Validating_Clustering_Models_Unsupervised_Machine_Learning
Reference Link: https://en.wikipedia.org/wiki/Silhouette_(clustering)#:~:text=The%20silhouette%20value%20is%20a,poorly%20matched%20to%20neighboring%20clusters.
https://scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_analysis.html#sphx-glr-auto-examples-cluster-plot-kmeans-silhouette-analysis-py
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- published: 25 Aug 2020
- views: 48550
9:45
Silhouette Method for Right K || Lesson 108 || Machine Learning || Learning Monkey ||
- Order: Reorder
- Duration: 9:45
- Uploaded Date: 07 Sep 2020
- views: 3334
#machinelearning#learningmonkey
In this class, we discuss the silhouette method for right k.
This is a measure of how well the give data point belongs to the ...
#machinelearning#learningmonkey
In this class, we discuss the silhouette method for right k.
This is a measure of how well the give data point belongs to the cluster.
After applying k means clustering we get different clusters.
We take a data point and measure the mean distance of this data point to all other data points in the cluster.
This gives how well this data point belongs to this cluster.
In the same way, calculate the mean distance of the point to all other data points in the nearest cluster.
This gives how dissimilar this data point belongs to other clusters.
Now we define a silhouette value to the point.
This value is between -1 and 1
Calculate all the data points and sum them.
We pick the best k for which the value is higher.
Link for playlists:
https://www.youtube.com/channel/UCl8x4Pn9Mnh_C1fue-Yndig/playlists
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https://wn.com/Silhouette_Method_For_Right_K_||_Lesson_108_||_Machine_Learning_||_Learning_Monkey_||
#machinelearning#learningmonkey
In this class, we discuss the silhouette method for right k.
This is a measure of how well the give data point belongs to the cluster.
After applying k means clustering we get different clusters.
We take a data point and measure the mean distance of this data point to all other data points in the cluster.
This gives how well this data point belongs to this cluster.
In the same way, calculate the mean distance of the point to all other data points in the nearest cluster.
This gives how dissimilar this data point belongs to other clusters.
Now we define a silhouette value to the point.
This value is between -1 and 1
Calculate all the data points and sum them.
We pick the best k for which the value is higher.
Link for playlists:
https://www.youtube.com/channel/UCl8x4Pn9Mnh_C1fue-Yndig/playlists
Link for our website: https://learningmonkey.in
Follow us on Facebook @ https://www.facebook.com/learningmonkey
Follow us on Instagram @ https://www.instagram.com/learningmonkey1/
Follow us on Twitter @ https://twitter.com/_learningmonkey
Mail us @ [email protected]
- published: 07 Sep 2020
- views: 3334
5:02
Find the number of clusters in KMeans. Silhouette score. Python code example
- Order: Reorder
- Duration: 5:02
- Uploaded Date: 23 Apr 2020
- views: 19425
Silhouette score is the metric that can find the optimal number of clusters in your data by using KMeans algorithm for clustering. Quick remind - Kmeans is an u...
Silhouette score is the metric that can find the optimal number of clusters in your data by using KMeans algorithm for clustering. Quick remind - Kmeans is an unsupervised learning in the area of Machine learning.
With this video I explain and demonstrate how Silhouette score and curve works in real data. If you are working with clustering algorithms, probably you know the situation when you are not sure how many cluster to use is the best for your data science project if using classical Elbow method. Silhouette score is a good replacement for this.
The silhouette value is a measure of how similar an object is to its own cluster (cohesion) compared to other clusters (separation). The silhouette ranges from −1 to +1, where a high value indicates that the object is well matched to its own cluster and poorly matched to neighboring clusters. In simple words, the silhouette score technique predict the number of clusters that corresponds your data the best.
Silhouette technique in Kmeans also provide Silhouette diagram which let you quickly take a look to statistical distribution of data clusters in the different scenarios of number of clusters.
Content of the video:
0:05 - Introduction to Silqouette score.
1:16 - Coding part in Python (Kmeans - Elbow method vs. Silhouette score, Silhouette curve and values).
4:37 - Silhouette diagrams.
In Python, scikit-learn provides the core of Silhouette score functionality on your hands.
Where I found this technique? That is perfect book to learn Python, Machine learning and Deep Learning: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron. Check my review on this book here: https://www.youtube.com/watch?v=nTadOuomhck
Wishes! - Vytautas
#kmeans
#unsupervisedlearning
#silhouettescore
https://wn.com/Find_The_Number_Of_Clusters_In_Kmeans._Silhouette_Score._Python_Code_Example
Silhouette score is the metric that can find the optimal number of clusters in your data by using KMeans algorithm for clustering. Quick remind - Kmeans is an unsupervised learning in the area of Machine learning.
With this video I explain and demonstrate how Silhouette score and curve works in real data. If you are working with clustering algorithms, probably you know the situation when you are not sure how many cluster to use is the best for your data science project if using classical Elbow method. Silhouette score is a good replacement for this.
The silhouette value is a measure of how similar an object is to its own cluster (cohesion) compared to other clusters (separation). The silhouette ranges from −1 to +1, where a high value indicates that the object is well matched to its own cluster and poorly matched to neighboring clusters. In simple words, the silhouette score technique predict the number of clusters that corresponds your data the best.
Silhouette technique in Kmeans also provide Silhouette diagram which let you quickly take a look to statistical distribution of data clusters in the different scenarios of number of clusters.
Content of the video:
0:05 - Introduction to Silqouette score.
1:16 - Coding part in Python (Kmeans - Elbow method vs. Silhouette score, Silhouette curve and values).
4:37 - Silhouette diagrams.
In Python, scikit-learn provides the core of Silhouette score functionality on your hands.
Where I found this technique? That is perfect book to learn Python, Machine learning and Deep Learning: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron. Check my review on this book here: https://www.youtube.com/watch?v=nTadOuomhck
Wishes! - Vytautas
#kmeans
#unsupervisedlearning
#silhouettescore
- published: 23 Apr 2020
- views: 19425
1:34
silhouette score for kmeans clustering
- Order: Reorder
- Duration: 1:34
- Uploaded Date: 11 Mar 2022
- views: 327
In our clustering analysis we use the Silhouette Score and typically comparing them across various numbers of clusters to help understand which works the best. ...
In our clustering analysis we use the Silhouette Score and typically comparing them across various numbers of clusters to help understand which works the best. Here we will use the yellowbrick library.
This is meant to be a showcase of how I approach data science. If you're interested in learning more visit my profile to reserve a class now. Send me a message to get a copy of my full syllabus for my programs: basic python, data analyst, data science.
Get a discount on your first class with this link.
https://preply.com/en/?pref=NDU3ODY5OQ==
Access the workbook here.
https://github.com/brandynewanek/guided_projects/blob/main/KaggleYouTube_project1_Pokemon.ipynb
https://wn.com/Silhouette_Score_For_Kmeans_Clustering
In our clustering analysis we use the Silhouette Score and typically comparing them across various numbers of clusters to help understand which works the best. Here we will use the yellowbrick library.
This is meant to be a showcase of how I approach data science. If you're interested in learning more visit my profile to reserve a class now. Send me a message to get a copy of my full syllabus for my programs: basic python, data analyst, data science.
Get a discount on your first class with this link.
https://preply.com/en/?pref=NDU3ODY5OQ==
Access the workbook here.
https://github.com/brandynewanek/guided_projects/blob/main/KaggleYouTube_project1_Pokemon.ipynb
- published: 11 Mar 2022
- views: 327
18:01
R- studio - K means clustering Using GAP ,Elbow and Silhouette method part 2
- Order: Reorder
- Duration: 18:01
- Uploaded Date: 11 May 2021
- views: 6002
- published: 11 May 2021
- views: 6002
8:12
0405 Number of Clusters as a Hyperparameter The Elbow and Silhouette Method
published: 07 Jun 2019
0405 Number of Clusters as a Hyperparameter The Elbow and Silhouette Method
0405 Number of Clusters as a Hyperparameter The Elbow and Silhouette Method
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- published: 07 Jun 2019
- views: 25521
9:18
Silhouette Score for clustering Explained | Silhouette (clustering)- Validating Clustering Models
Silhouette Score for clustering Explained | Silhouette (clustering)- Validating Clustering...
published: 20 May 2021
Silhouette Score for clustering Explained | Silhouette (clustering)- Validating Clustering Models
Silhouette Score for clustering Explained | Silhouette (clustering)- Validating Clustering Models
- Report rights infringement
- published: 20 May 2021
- views: 47821
Silhouette Score for clustering Explained | Silhouette (clustering)- Validating Clustering Models
#SilhouetteScore #UnfoldDataScience
Hello ,
My name is Aman and I am a Data Scientist.
About this video:
In this video, I speak about Silhouette Score and explain step by step how Silhouette Score works for cluster validation. I explain how to validate clusters and how to measure goodness of clusters. I explain the mathematical formula of Silhouette Score and intuition behind it. Below points are discussed in this video:
1. Silhouette Score for clustering
2. Validation on K-means clusters
3. Cluster validation techniques
4. How to measure goodness of clusters
5. Unsupervised machine learning accuracy
About Unfold Data science: This channel is to help people understand basics of data science through simple examples in easy way. Anybody without having prior knowledge of computer programming or statistics or machine learning and artificial intelligence can get an understanding of data science at high level through this channel. The videos uploaded will not be very technical in nature and hence it can be easily grasped by viewers from different background as well.
If you need Data Science training from scratch . Please fill this form (Please Note: Training is chargeable)
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Category 1 - Must Read For Every Data Scientist:
The Elements of Statistical Learning by Trevor Hastie - https://amzn.to/37wMo9H
Python Data Science Handbook - https://amzn.to/31UCScm
Business Statistics By Ken Black - https://amzn.to/2LObAA5
Hands-On Machine Learning with Scikit Learn, Keras, and TensorFlow by Aurelien Geron - https://amzn.to/3gV8sO9
Ctaegory 2 - Overall Data Science:
The Art of Data Science By Roger D. Peng - https://amzn.to/2KD75aD
Predictive Analytics By By Eric Siegel - https://amzn.to/3nsQftV
Data Science for Business By Foster Provost - https://amzn.to/3ajN8QZ
Category 3 - Statistics and Mathematics:
Naked Statistics By Charles Wheelan - https://amzn.to/3gXLdmp
Practical Statistics for Data Scientist By Peter Bruce - https://amzn.to/37wL9Y5
Category 4 - Machine Learning:
Introduction to machine learning by Andreas C Muller - https://amzn.to/3oZ3X7T
The Hundred Page Machine Learning Book by Andriy Burkov - https://amzn.to/3pdqCxJ
Category 5 - Programming:
The Pragmatic Programmer by David Thomas - https://amzn.to/2WqWXVj
Clean Code by Robert C. Martin - https://amzn.to/3oYOdlt
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Watch python for data science playlist here:
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Learn Ensemble Model, Bagging and Boosting here:
https://www.youtube.com/watch?v=fuO6QXAo-5M&list=PLmPJQXJiMoUWfMvIqAn0VI_LHlw4AmVrb
Build Career in Data Science Playlist:
https://www.youtube.com/watch?v=9pytkbvF8AU&list=PLmPJQXJiMoUWoG8fRUXPRcZec9LgdHmCL
Artificial Neural Network and Deep Learning Playlist:
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7:09
Machine Learning | Silhouette Coefficient
Silhouette refers to a method of interpretation and validation of consistency within clust...
published: 16 Nov 2019
Machine Learning | Silhouette Coefficient
Machine Learning | Silhouette Coefficient
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- published: 16 Nov 2019
- views: 24961
Silhouette refers to a method of interpretation and validation of consistency within clusters of data. The technique provides a succinct graphical representation of how well each object has been classified. #MachineLearning #SilhouetteCoefficient
Machine Learning 👉https://www.youtube.com/playlist?list=PLPN-43XehstOjGY6vM6nBpSggHoAv9hkR
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6:02
How to Compute Silhouette Coefficient – K Means Clustering in Machine Learning by Mahesh Huddar
How to Compute Silhouette Coefficient – K Means Clustering in Machine Learning by Mahesh H...
published: 22 Feb 2023
How to Compute Silhouette Coefficient – K Means Clustering in Machine Learning by Mahesh Huddar
How to Compute Silhouette Coefficient – K Means Clustering in Machine Learning by Mahesh Huddar
- Report rights infringement
- published: 22 Feb 2023
- views: 8341
How to Compute Silhouette Coefficient – K Means Clustering in Machine Learning by Mahesh Huddar
The following concepts are discussed:
______________________________
How to Compute Silhouette Coefficient,
K Means Clustering,
Silhouette Coefficient in Machine Learning,
Silhouette Coefficient in data mining,
Silhouette Coefficient K Means Clustering
********************************
1. Blog / Website: https://www.vtupulse.com/
2. Like Facebook Page: https://www.facebook.com/VTUPulse
3. Follow us on Instagram: https://www.instagram.com/vtupulse/
4. Like, Share, Subscribe, and Don't forget to press the bell ICON for regular updates
20:07
Silhouette (clustering)- Validating Clustering Models- Unsupervised Machine Learning
Reference Link: https://en.wikipedia.org/wiki/Silhouette_(clustering)#:~:text=The%20silhou...
published: 25 Aug 2020
Silhouette (clustering)- Validating Clustering Models- Unsupervised Machine Learning
Silhouette (clustering)- Validating Clustering Models- Unsupervised Machine Learning
- Report rights infringement
- published: 25 Aug 2020
- views: 48550
Reference Link: https://en.wikipedia.org/wiki/Silhouette_(clustering)#:~:text=The%20silhouette%20value%20is%20a,poorly%20matched%20to%20neighboring%20clusters.
https://scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_analysis.html#sphx-glr-auto-examples-cluster-plot-kmeans-silhouette-analysis-py
github: https://github.com/krishnaik06/Silhouette-clustering-
Please donate if you want to support the channel through GPay UPID,
Gpay: krishnaik06@okicici
Discord Server Link: https://discord.gg/tvAJuuy
Telegram link: https://t.me/joinchat/N77M7xRvYUd403DgfE4TWw
Please join as a member in my channel to get additional benefits like materials in Data Science, live streaming for Members and many more
https://www.youtube.com/channel/UCNU_lfiiWBdtULKOw6X0Dig/join
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9:45
Silhouette Method for Right K || Lesson 108 || Machine Learning || Learning Monkey ||
#machinelearning#learningmonkey
In this class, we discuss the silhouette method for righ...
published: 07 Sep 2020
Silhouette Method for Right K || Lesson 108 || Machine Learning || Learning Monkey ||
Silhouette Method for Right K || Lesson 108 || Machine Learning || Learning Monkey ||
- Report rights infringement
- published: 07 Sep 2020
- views: 3334
#machinelearning#learningmonkey
In this class, we discuss the silhouette method for right k.
This is a measure of how well the give data point belongs to the cluster.
After applying k means clustering we get different clusters.
We take a data point and measure the mean distance of this data point to all other data points in the cluster.
This gives how well this data point belongs to this cluster.
In the same way, calculate the mean distance of the point to all other data points in the nearest cluster.
This gives how dissimilar this data point belongs to other clusters.
Now we define a silhouette value to the point.
This value is between -1 and 1
Calculate all the data points and sum them.
We pick the best k for which the value is higher.
Link for playlists:
https://www.youtube.com/channel/UCl8x4Pn9Mnh_C1fue-Yndig/playlists
Link for our website: https://learningmonkey.in
Follow us on Facebook @ https://www.facebook.com/learningmonkey
Follow us on Instagram @ https://www.instagram.com/learningmonkey1/
Follow us on Twitter @ https://twitter.com/_learningmonkey
Mail us @ [email protected]
5:02
Find the number of clusters in KMeans. Silhouette score. Python code example
Silhouette score is the metric that can find the optimal number of clusters in your data b...
published: 23 Apr 2020
Find the number of clusters in KMeans. Silhouette score. Python code example
Find the number of clusters in KMeans. Silhouette score. Python code example
- Report rights infringement
- published: 23 Apr 2020
- views: 19425
Silhouette score is the metric that can find the optimal number of clusters in your data by using KMeans algorithm for clustering. Quick remind - Kmeans is an unsupervised learning in the area of Machine learning.
With this video I explain and demonstrate how Silhouette score and curve works in real data. If you are working with clustering algorithms, probably you know the situation when you are not sure how many cluster to use is the best for your data science project if using classical Elbow method. Silhouette score is a good replacement for this.
The silhouette value is a measure of how similar an object is to its own cluster (cohesion) compared to other clusters (separation). The silhouette ranges from −1 to +1, where a high value indicates that the object is well matched to its own cluster and poorly matched to neighboring clusters. In simple words, the silhouette score technique predict the number of clusters that corresponds your data the best.
Silhouette technique in Kmeans also provide Silhouette diagram which let you quickly take a look to statistical distribution of data clusters in the different scenarios of number of clusters.
Content of the video:
0:05 - Introduction to Silqouette score.
1:16 - Coding part in Python (Kmeans - Elbow method vs. Silhouette score, Silhouette curve and values).
4:37 - Silhouette diagrams.
In Python, scikit-learn provides the core of Silhouette score functionality on your hands.
Where I found this technique? That is perfect book to learn Python, Machine learning and Deep Learning: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron. Check my review on this book here: https://www.youtube.com/watch?v=nTadOuomhck
Wishes! - Vytautas
#kmeans
#unsupervisedlearning
#silhouettescore
1:34
silhouette score for kmeans clustering
In our clustering analysis we use the Silhouette Score and typically comparing them across...
published: 11 Mar 2022
silhouette score for kmeans clustering
silhouette score for kmeans clustering
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- published: 11 Mar 2022
- views: 327
In our clustering analysis we use the Silhouette Score and typically comparing them across various numbers of clusters to help understand which works the best. Here we will use the yellowbrick library.
This is meant to be a showcase of how I approach data science. If you're interested in learning more visit my profile to reserve a class now. Send me a message to get a copy of my full syllabus for my programs: basic python, data analyst, data science.
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Access the workbook here.
https://github.com/brandynewanek/guided_projects/blob/main/KaggleYouTube_project1_Pokemon.ipynb
18:01
R- studio - K means clustering Using GAP ,Elbow and Silhouette method part 2
published: 11 May 2021
R- studio - K means clustering Using GAP ,Elbow and Silhouette method part 2
R- studio - K means clustering Using GAP ,Elbow and Silhouette method part 2
- Report rights infringement
- published: 11 May 2021
- views: 6002
Silhouette
A silhouette is the image of a person, animal, object or scene represented as a solid shape of a single color, usually black, its edges matching the outline of the subject. The interior of a silhouette is featureless, and the whole is typically presented on a light background, usually white, or none at all. The silhouette differs from an outline, which depicts the edge of an object in a linear form, while a silhouette appears as a solid shape. Silhouette images may be created in any visual artistic media, but was first used to describe pieces of cut paper, which were then stuck to a backing in a contrasting colour, and often framed.
Cutting portraits, generally in profile, from black card became popular in the mid-18th century, though the term silhouette was seldom used until the early decades of the 19th century, and the tradition has continued under this name into the 21st century. They represented a cheap but effective alternative to the portrait miniature, and skilled specialist artists could cut a high-quality bust portrait, by far the most common style, in a matter of minutes, working purely by eye. Other artists, especially from about 1790, drew an outline on paper, then painted it in, which could be equally quick. The leading 18th-century English "profilist" in painting, John Miers, advertised "three minute sittings", and the cost might be as low as half a crown around 1800. Miers' superior products could be in grisaille, with delicate highlights added in gold or yellow, and some examples might be painted on various backings, including gesso, glass or ivory. The size was normally small, with many designed to fit into a locket, but otherwise a bust some 3 to 5 inches high was typical, with half- or full-length portraits proportionately larger.
This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Silhouette
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