-
Multidimensional Scaling
In this video we introduce Multidimensional scaling (MDS), an alternative tool for presenting data and reducing dimensionality. We show how to map data with distances, create insightful visualizations of our data and compare this algorithm with PCA.
This video is a part of Introduction to Data Science video series that dives into machine learning, visual analytics, and joys of interactive data analysis using Orange Data Mining software (https://orangedatamining.com).
SUBSCRIBE to our channel: http://youtube.com/orangedatamining
The development of this video series was supported by grants from the Slovenian Research Agency (including P2-0209, V2-2274, and L2-3170), Slovenia Ministry of Digital Transformation, European Union (including xAIM and ARISA) and Google.org/Tides foundation.
#...
published: 18 Aug 2023
-
StatQuest: MDS and PCoA
MDS (multi-dimensional scaling) and PCoA (principal coordinate analysis) are very, very similar to PCA (principal component analysis). There really only one small difference, but that difference means you need to know what you're doing if you're going to use MDS effectively. This video make sure you learn what you need to know to use MDS and PCoA.
There is a minor error at 4:14: The difference for gene 3 should be (2.2 - 1)². Instead the distance for gene 2 was repeated.
For a complete index of all the StatQuest videos, check out:
https://statquest.org/video-index/
If you'd like to support StatQuest, please consider...
Buying The StatQuest Illustrated Guide to Machine Learning!!!
PDF - https://statquest.gumroad.com/l/wvtmc
Paperback - https://www.amazon.com/dp/B09ZCKR4H6
Kindle eBook -...
published: 11 Dec 2017
-
Data Mining - Principal Component Analysis (PCA) and Multidimensional Scaling (MDS) in 7 MINUTES
This video gives the key takeaways on the Curse of Dimensionality and two dimension reduction techniques: Principal Component Analysis and Multidimensional Scaling. Dimension reduction techniques can be used to tell us which variables in our data are most important. Principal Component Analysis (PCA) and Multidimensional Scaling (MDS) are useful data analysis techniques that every Statistican and Data Scientist ought to know.
In this video, we go over the main ideas behind PCA and MDS in order to give an intuitive sense of the methods.
0:00 - The Curse of Dimensionality (COD) and "Dimension Reduction"
1:05 - Principal Components Analysis (PCA)
3:11 - Multidimensional Scaling (MDS)
published: 01 Feb 2021
-
Multi-Dimensional Scaling (MDS): Statistics | Psychology Lectures @ doorsteptutor.com
Statistics Lectures @ https://www.doorsteptutor.com/Subjects/Statistics/Lectures/
NET Preparation: https://www.doorsteptutor.com/Exams/UGC/
CUET PG: https://www.doorsteptutor.com/Exams/CUET/PG/
IAS Mains: https://www.doorsteptutor.com/Exams/IAS/Mains/
GATE: https://www.doorsteptutor.com/Exams/GATE/
NTA NET Paper 1 Lectures - https://www.doorsteptutor.com/Exams/UGC/Paper-1/Lectures/
NTA NET Paper 1 Mock papers - https://www.doorsteptutor.com/Exams/UGC/Paper-1/Online-Test-Series/
NTA NET Paper 1 Practice questions - https://www.doorsteptutor.com/Exams/UGC/Paper-1/Questions/
NTA NET Paper 1 Postal Course - https://www.examrace.com/NTA-UGC-NET/NTA-UGC-NET-FlexiPrep-Program/Postal-Courses/Examrace-NTA-UGC-NET-Paper-I-Series.htm
NCERT, Yojana, Kurukshetra, Down to Earth, Science, Social...
published: 01 Jan 2023
-
What is Multidimensional Scaling in Machine Learning?
Welcome to our in-depth exploration of Multidimensional Scaling (MDS) in Machine Learning. As we continue our journey through the fascinating landscape of data science, we're going to take a deep dive into one of the most powerful techniques that data scientists use to make sense of complex, high-dimensional data.
Multidimensional Scaling, or MDS as it is commonly known, is a technique that allows us to visualize the pattern of proximities (i.e., similarities or distances) among a set of objects, in a low-dimensional space, usually in two or three dimensions. The beauty of this technique lies in its ability to simplify the complexity of multi-dimensional data, enabling us to see patterns and relationships that would be impossible to perceive in a higher-dimensional space.
OUTLINE:
00:00:...
published: 14 Oct 2023
-
Multidimensional Scaling Analysis using SPSS # Perceptual Maps
Multidimensional Scaling Analysis using SPSS:
In this video, I have explained about Multidimensional Scaling in a simple and easy way using an example.
This Multidimensional Scaling analysis mostly used in Marketing research. So, I have taken a Consumer behavior case study and explained the complete analysis from Questionnaire, Data collection, Data entry in SPSS, Data analysis, and explained the interpretation part also.
Please, like and share the video with the other research scholars and Subscribe to the channel.
published: 27 Aug 2020
-
08c Machine Learning: Multidimensional Scaling
Lecture on multidimensional scaling for feature projection. Reduce the dimensionality while preserving the dissimilarity between the training samples.
Follow along with the demonstration workflow in Python's scikit-learn package:
https://github.com/GeostatsGuy/PythonNumericalDemos/blob/master/SubsurfaceDataAnalytics_Multidimensional_Scaling.ipynb
published: 29 Sep 2019
-
Lecture 39- Multi Dimensional Scaling
To access the translated content:
1. The translated content of this course is available in regional languages. For details please visit https://nptel.ac.in/translation
The video course content can be accessed in the form of regional language text transcripts, books which can be accessed under downloads of each course, subtitles in the video and Video Text Track below the video.
Your feedback is highly appreciated. Kindly fill this form https://forms.gle/XFZhSnHsCLML2LXA6
2. Regional language subtitles available for this course
To watch the subtitles in regional languages:
1. Click on the lecture under Course Details.
2. Play the video.
3. Now click on the Settings icon and a list of features will display
4. From that select the option Subtitles/CC.
5. Now select the Language fro...
published: 10 Sep 2017
-
Multidimensional Scaling: Classical Metric
Belajar Olah Data menggunakan Multidimensional Scaling: Classical Metric, dengan SPSS versi 22
published: 30 Nov 2024
-
Multidimensional Scaling (MDS) | Dimensionality Reduction Techniques (3/5)
To try everything Brilliant has to offer—free—for a full 30 days, visit https://brilliant.org/DeepFindr . The first 200 of you will get 20% off Brilliant’s annual premium subscription
▬▬ Papers / Resources ▬▬▬
Colab Notebook: https://colab.research.google.com/drive/1n_kdyXsA60djl-nTSUxLQTZuKcxkMA83?usp=sharing
Kruskal Paper 1964: http://cda.psych.uiuc.edu/psychometrika_highly_cited_articles/kruskal_1964a.pdf
Very old MDS Website: http://www.analytictech.com/borgatti/mds.htm
Rearrange Scalar Product:
- https://www.sjsu.edu/faculty/guangliang.chen/Math250/lec10mds.pdf
- https://github.com/drewwilimitis/Manifold-Learning/blob/master/Multidimensional_Scaling.ipynb
Metrics Blog Post: https://towardsdatascience.com/9-distance-measures-in-data-science-918109d069fa
Proof that MDS has no unique ...
published: 16 Jan 2024
6:21
Multidimensional Scaling
In this video we introduce Multidimensional scaling (MDS), an alternative tool for presenting data and reducing dimensionality. We show how to map data with dis...
In this video we introduce Multidimensional scaling (MDS), an alternative tool for presenting data and reducing dimensionality. We show how to map data with distances, create insightful visualizations of our data and compare this algorithm with PCA.
This video is a part of Introduction to Data Science video series that dives into machine learning, visual analytics, and joys of interactive data analysis using Orange Data Mining software (https://orangedatamining.com).
SUBSCRIBE to our channel: http://youtube.com/orangedatamining
The development of this video series was supported by grants from the Slovenian Research Agency (including P2-0209, V2-2274, and L2-3170), Slovenia Ministry of Digital Transformation, European Union (including xAIM and ARISA) and Google.org/Tides foundation.
#machinelearning #orange #visualanalytics #datamining
__
Written by: Blaž Zupan (http://biolab.si/blaz)
Presented by: Noah Novšak
Production and edit: Lara Zupan
Intro/outro: Agnieszka Rovšnik
Music by: Damjan Jović – Dravlje Rec
Orange is developed by Biolab at University of Ljubljana (https://www.biolab.si)
https://wn.com/Multidimensional_Scaling
In this video we introduce Multidimensional scaling (MDS), an alternative tool for presenting data and reducing dimensionality. We show how to map data with distances, create insightful visualizations of our data and compare this algorithm with PCA.
This video is a part of Introduction to Data Science video series that dives into machine learning, visual analytics, and joys of interactive data analysis using Orange Data Mining software (https://orangedatamining.com).
SUBSCRIBE to our channel: http://youtube.com/orangedatamining
The development of this video series was supported by grants from the Slovenian Research Agency (including P2-0209, V2-2274, and L2-3170), Slovenia Ministry of Digital Transformation, European Union (including xAIM and ARISA) and Google.org/Tides foundation.
#machinelearning #orange #visualanalytics #datamining
__
Written by: Blaž Zupan (http://biolab.si/blaz)
Presented by: Noah Novšak
Production and edit: Lara Zupan
Intro/outro: Agnieszka Rovšnik
Music by: Damjan Jović – Dravlje Rec
Orange is developed by Biolab at University of Ljubljana (https://www.biolab.si)
- published: 18 Aug 2023
- views: 13564
8:18
StatQuest: MDS and PCoA
MDS (multi-dimensional scaling) and PCoA (principal coordinate analysis) are very, very similar to PCA (principal component analysis). There really only one sma...
MDS (multi-dimensional scaling) and PCoA (principal coordinate analysis) are very, very similar to PCA (principal component analysis). There really only one small difference, but that difference means you need to know what you're doing if you're going to use MDS effectively. This video make sure you learn what you need to know to use MDS and PCoA.
There is a minor error at 4:14: The difference for gene 3 should be (2.2 - 1)². Instead the distance for gene 2 was repeated.
For a complete index of all the StatQuest videos, check out:
https://statquest.org/video-index/
If you'd like to support StatQuest, please consider...
Buying The StatQuest Illustrated Guide to Machine Learning!!!
PDF - https://statquest.gumroad.com/l/wvtmc
Paperback - https://www.amazon.com/dp/B09ZCKR4H6
Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC
Patreon: https://www.patreon.com/statquest
...or...
YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join
...a cool StatQuest t-shirt or sweatshirt:
https://shop.spreadshirt.com/statquest-with-josh-starmer/
...buying one or two of my songs (or go large and get a whole album!)
https://joshuastarmer.bandcamp.com/
...or just donating to StatQuest!
https://www.paypal.me/statquest
Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:
https://twitter.com/joshuastarmer
#statquest #MDS #PCoA
https://wn.com/Statquest_Mds_And_Pcoa
MDS (multi-dimensional scaling) and PCoA (principal coordinate analysis) are very, very similar to PCA (principal component analysis). There really only one small difference, but that difference means you need to know what you're doing if you're going to use MDS effectively. This video make sure you learn what you need to know to use MDS and PCoA.
There is a minor error at 4:14: The difference for gene 3 should be (2.2 - 1)². Instead the distance for gene 2 was repeated.
For a complete index of all the StatQuest videos, check out:
https://statquest.org/video-index/
If you'd like to support StatQuest, please consider...
Buying The StatQuest Illustrated Guide to Machine Learning!!!
PDF - https://statquest.gumroad.com/l/wvtmc
Paperback - https://www.amazon.com/dp/B09ZCKR4H6
Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC
Patreon: https://www.patreon.com/statquest
...or...
YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join
...a cool StatQuest t-shirt or sweatshirt:
https://shop.spreadshirt.com/statquest-with-josh-starmer/
...buying one or two of my songs (or go large and get a whole album!)
https://joshuastarmer.bandcamp.com/
...or just donating to StatQuest!
https://www.paypal.me/statquest
Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:
https://twitter.com/joshuastarmer
#statquest #MDS #PCoA
- published: 11 Dec 2017
- views: 195831
7:08
Data Mining - Principal Component Analysis (PCA) and Multidimensional Scaling (MDS) in 7 MINUTES
This video gives the key takeaways on the Curse of Dimensionality and two dimension reduction techniques: Principal Component Analysis and Multidimensional Scal...
This video gives the key takeaways on the Curse of Dimensionality and two dimension reduction techniques: Principal Component Analysis and Multidimensional Scaling. Dimension reduction techniques can be used to tell us which variables in our data are most important. Principal Component Analysis (PCA) and Multidimensional Scaling (MDS) are useful data analysis techniques that every Statistican and Data Scientist ought to know.
In this video, we go over the main ideas behind PCA and MDS in order to give an intuitive sense of the methods.
0:00 - The Curse of Dimensionality (COD) and "Dimension Reduction"
1:05 - Principal Components Analysis (PCA)
3:11 - Multidimensional Scaling (MDS)
https://wn.com/Data_Mining_Principal_Component_Analysis_(Pca)_And_Multidimensional_Scaling_(Mds)_In_7_Minutes
This video gives the key takeaways on the Curse of Dimensionality and two dimension reduction techniques: Principal Component Analysis and Multidimensional Scaling. Dimension reduction techniques can be used to tell us which variables in our data are most important. Principal Component Analysis (PCA) and Multidimensional Scaling (MDS) are useful data analysis techniques that every Statistican and Data Scientist ought to know.
In this video, we go over the main ideas behind PCA and MDS in order to give an intuitive sense of the methods.
0:00 - The Curse of Dimensionality (COD) and "Dimension Reduction"
1:05 - Principal Components Analysis (PCA)
3:11 - Multidimensional Scaling (MDS)
- published: 01 Feb 2021
- views: 18856
4:34
Multi-Dimensional Scaling (MDS): Statistics | Psychology Lectures @ doorsteptutor.com
Statistics Lectures @ https://www.doorsteptutor.com/Subjects/Statistics/Lectures/
NET Preparation: https://www.doorsteptutor.com/Exams/UGC/
CUET PG: https://w...
Statistics Lectures @ https://www.doorsteptutor.com/Subjects/Statistics/Lectures/
NET Preparation: https://www.doorsteptutor.com/Exams/UGC/
CUET PG: https://www.doorsteptutor.com/Exams/CUET/PG/
IAS Mains: https://www.doorsteptutor.com/Exams/IAS/Mains/
GATE: https://www.doorsteptutor.com/Exams/GATE/
NTA NET Paper 1 Lectures - https://www.doorsteptutor.com/Exams/UGC/Paper-1/Lectures/
NTA NET Paper 1 Mock papers - https://www.doorsteptutor.com/Exams/UGC/Paper-1/Online-Test-Series/
NTA NET Paper 1 Practice questions - https://www.doorsteptutor.com/Exams/UGC/Paper-1/Questions/
NTA NET Paper 1 Postal Course - https://www.examrace.com/NTA-UGC-NET/NTA-UGC-NET-FlexiPrep-Program/Postal-Courses/Examrace-NTA-UGC-NET-Paper-I-Series.htm
NCERT, Yojana, Kurukshetra, Down to Earth, Science, Social Studies and More interesting topics subscribe at Examrace: https://www.youtube.com/c/Examrace
NCERT, Yojana, Kurukshetra, Down to Earth, Science, Social Studies and More interesting topics subscribe at ExamraceHindi: https://www.youtube.com/c/ExamraceHindi
For classes nursery to class 5 videos subscribe to FunProf: https://www.youtube.com/c/FunProf
For Science Class 11-12 and important topics subscribe to DoorStepTutor: https://www.youtube.com/c/DoorstepTutor #ugcnet #doorsteptutor #examrace
https://wn.com/Multi_Dimensional_Scaling_(Mds)_Statistics_|_Psychology_Lectures_Doorsteptutor.Com
Statistics Lectures @ https://www.doorsteptutor.com/Subjects/Statistics/Lectures/
NET Preparation: https://www.doorsteptutor.com/Exams/UGC/
CUET PG: https://www.doorsteptutor.com/Exams/CUET/PG/
IAS Mains: https://www.doorsteptutor.com/Exams/IAS/Mains/
GATE: https://www.doorsteptutor.com/Exams/GATE/
NTA NET Paper 1 Lectures - https://www.doorsteptutor.com/Exams/UGC/Paper-1/Lectures/
NTA NET Paper 1 Mock papers - https://www.doorsteptutor.com/Exams/UGC/Paper-1/Online-Test-Series/
NTA NET Paper 1 Practice questions - https://www.doorsteptutor.com/Exams/UGC/Paper-1/Questions/
NTA NET Paper 1 Postal Course - https://www.examrace.com/NTA-UGC-NET/NTA-UGC-NET-FlexiPrep-Program/Postal-Courses/Examrace-NTA-UGC-NET-Paper-I-Series.htm
NCERT, Yojana, Kurukshetra, Down to Earth, Science, Social Studies and More interesting topics subscribe at Examrace: https://www.youtube.com/c/Examrace
NCERT, Yojana, Kurukshetra, Down to Earth, Science, Social Studies and More interesting topics subscribe at ExamraceHindi: https://www.youtube.com/c/ExamraceHindi
For classes nursery to class 5 videos subscribe to FunProf: https://www.youtube.com/c/FunProf
For Science Class 11-12 and important topics subscribe to DoorStepTutor: https://www.youtube.com/c/DoorstepTutor #ugcnet #doorsteptutor #examrace
- published: 01 Jan 2023
- views: 10282
2:43
What is Multidimensional Scaling in Machine Learning?
Welcome to our in-depth exploration of Multidimensional Scaling (MDS) in Machine Learning. As we continue our journey through the fascinating landscape of data ...
Welcome to our in-depth exploration of Multidimensional Scaling (MDS) in Machine Learning. As we continue our journey through the fascinating landscape of data science, we're going to take a deep dive into one of the most powerful techniques that data scientists use to make sense of complex, high-dimensional data.
Multidimensional Scaling, or MDS as it is commonly known, is a technique that allows us to visualize the pattern of proximities (i.e., similarities or distances) among a set of objects, in a low-dimensional space, usually in two or three dimensions. The beauty of this technique lies in its ability to simplify the complexity of multi-dimensional data, enabling us to see patterns and relationships that would be impossible to perceive in a higher-dimensional space.
OUTLINE:
00:00:00 Introduction to Multidimensional Scaling
00:00:15 The Concept of Multidimensional Scaling
00:00:32 How Multidimensional Scaling Works
00:01:22 The Power of Multidimensional Scaling
00:01:39 Recap of Key Points
00:02:23 Conclusion
00:00:00 Introduction to Multidimensional Scaling
In this part, we will introduce you to the concept of Multidimensional Scaling and its importance in today's data-driven world. We will be discussing how it aids in simplifying complex datasets and provides a way to visualize multi-dimensional data in a two or three-dimensional space.
00:00:15 The Concept of Multidimensional Scaling
Here, we delve into the theoretical aspect of MDS. It's a set of statistical techniques used to visualize the level of similarity of individual cases of a dataset. MDS is particularly useful when the data collected doesn't lend itself well to traditional graphing methods. This section will provide an understanding of how MDS is a powerful tool for exploratory data analysis.
00:00:32 How Multidimensional Scaling Works
In this segment, we will dive deep into the mechanics of MDS. We will explain how it converts similarities/dissimilarities into a geometric representation. With a combination of visuals and detailed explanations, we will decode the algorithm behind MDS and demonstrate its implementation using Python.
00:01:22 The Power of Multidimensional Scaling
We will discuss various applications of MDS in diverse fields such as psychology, marketing research, and even bioinformatics. This section will shed light on how MDS can help in making sense of large, complex datasets and draw meaningful insights from them. We will also discuss some real-world examples where MDS has been instrumental in providing breakthrough insights.
00:01:39 Recap of Key Points
Having explored the theory and application of MDS, we will recap the key points covered in the video. This will reinforce your understanding of MDS and its significance in machine learning. We will also provide some additional resources for further study.
00:02:23 Conclusion
Finally, we will wrap up our guide on Multidimensional Scaling. We hope this video helps you grasp the concept of MDS and its application in machine learning. Stay tuned for more videos on advanced topics in data science and machine learning.
Please don't forget to like, share, and subscribe to our channel for more insightful content on machine learning and data science. Leave your questions or comments below, and we'll do our best to address them in upcoming videos.
Remember, understanding the world of data is just a click away!
https://wn.com/What_Is_Multidimensional_Scaling_In_Machine_Learning
Welcome to our in-depth exploration of Multidimensional Scaling (MDS) in Machine Learning. As we continue our journey through the fascinating landscape of data science, we're going to take a deep dive into one of the most powerful techniques that data scientists use to make sense of complex, high-dimensional data.
Multidimensional Scaling, or MDS as it is commonly known, is a technique that allows us to visualize the pattern of proximities (i.e., similarities or distances) among a set of objects, in a low-dimensional space, usually in two or three dimensions. The beauty of this technique lies in its ability to simplify the complexity of multi-dimensional data, enabling us to see patterns and relationships that would be impossible to perceive in a higher-dimensional space.
OUTLINE:
00:00:00 Introduction to Multidimensional Scaling
00:00:15 The Concept of Multidimensional Scaling
00:00:32 How Multidimensional Scaling Works
00:01:22 The Power of Multidimensional Scaling
00:01:39 Recap of Key Points
00:02:23 Conclusion
00:00:00 Introduction to Multidimensional Scaling
In this part, we will introduce you to the concept of Multidimensional Scaling and its importance in today's data-driven world. We will be discussing how it aids in simplifying complex datasets and provides a way to visualize multi-dimensional data in a two or three-dimensional space.
00:00:15 The Concept of Multidimensional Scaling
Here, we delve into the theoretical aspect of MDS. It's a set of statistical techniques used to visualize the level of similarity of individual cases of a dataset. MDS is particularly useful when the data collected doesn't lend itself well to traditional graphing methods. This section will provide an understanding of how MDS is a powerful tool for exploratory data analysis.
00:00:32 How Multidimensional Scaling Works
In this segment, we will dive deep into the mechanics of MDS. We will explain how it converts similarities/dissimilarities into a geometric representation. With a combination of visuals and detailed explanations, we will decode the algorithm behind MDS and demonstrate its implementation using Python.
00:01:22 The Power of Multidimensional Scaling
We will discuss various applications of MDS in diverse fields such as psychology, marketing research, and even bioinformatics. This section will shed light on how MDS can help in making sense of large, complex datasets and draw meaningful insights from them. We will also discuss some real-world examples where MDS has been instrumental in providing breakthrough insights.
00:01:39 Recap of Key Points
Having explored the theory and application of MDS, we will recap the key points covered in the video. This will reinforce your understanding of MDS and its significance in machine learning. We will also provide some additional resources for further study.
00:02:23 Conclusion
Finally, we will wrap up our guide on Multidimensional Scaling. We hope this video helps you grasp the concept of MDS and its application in machine learning. Stay tuned for more videos on advanced topics in data science and machine learning.
Please don't forget to like, share, and subscribe to our channel for more insightful content on machine learning and data science. Leave your questions or comments below, and we'll do our best to address them in upcoming videos.
Remember, understanding the world of data is just a click away!
- published: 14 Oct 2023
- views: 1456
8:34
Multidimensional Scaling Analysis using SPSS # Perceptual Maps
Multidimensional Scaling Analysis using SPSS:
In this video, I have explained about Multidimensional Scaling in a simple and easy way using an example.
This Mul...
Multidimensional Scaling Analysis using SPSS:
In this video, I have explained about Multidimensional Scaling in a simple and easy way using an example.
This Multidimensional Scaling analysis mostly used in Marketing research. So, I have taken a Consumer behavior case study and explained the complete analysis from Questionnaire, Data collection, Data entry in SPSS, Data analysis, and explained the interpretation part also.
Please, like and share the video with the other research scholars and Subscribe to the channel.
https://wn.com/Multidimensional_Scaling_Analysis_Using_Spss_Perceptual_Maps
Multidimensional Scaling Analysis using SPSS:
In this video, I have explained about Multidimensional Scaling in a simple and easy way using an example.
This Multidimensional Scaling analysis mostly used in Marketing research. So, I have taken a Consumer behavior case study and explained the complete analysis from Questionnaire, Data collection, Data entry in SPSS, Data analysis, and explained the interpretation part also.
Please, like and share the video with the other research scholars and Subscribe to the channel.
- published: 27 Aug 2020
- views: 40637
20:17
08c Machine Learning: Multidimensional Scaling
Lecture on multidimensional scaling for feature projection. Reduce the dimensionality while preserving the dissimilarity between the training samples.
Follow a...
Lecture on multidimensional scaling for feature projection. Reduce the dimensionality while preserving the dissimilarity between the training samples.
Follow along with the demonstration workflow in Python's scikit-learn package:
https://github.com/GeostatsGuy/PythonNumericalDemos/blob/master/SubsurfaceDataAnalytics_Multidimensional_Scaling.ipynb
https://wn.com/08C_Machine_Learning_Multidimensional_Scaling
Lecture on multidimensional scaling for feature projection. Reduce the dimensionality while preserving the dissimilarity between the training samples.
Follow along with the demonstration workflow in Python's scikit-learn package:
https://github.com/GeostatsGuy/PythonNumericalDemos/blob/master/SubsurfaceDataAnalytics_Multidimensional_Scaling.ipynb
- published: 29 Sep 2019
- views: 15753
34:59
Lecture 39- Multi Dimensional Scaling
To access the translated content:
1. The translated content of this course is available in regional languages. For details please visit https://nptel.ac.in/tra...
To access the translated content:
1. The translated content of this course is available in regional languages. For details please visit https://nptel.ac.in/translation
The video course content can be accessed in the form of regional language text transcripts, books which can be accessed under downloads of each course, subtitles in the video and Video Text Track below the video.
Your feedback is highly appreciated. Kindly fill this form https://forms.gle/XFZhSnHsCLML2LXA6
2. Regional language subtitles available for this course
To watch the subtitles in regional languages:
1. Click on the lecture under Course Details.
2. Play the video.
3. Now click on the Settings icon and a list of features will display
4. From that select the option Subtitles/CC.
5. Now select the Language from the available languages to read the subtitle in the regional language.
https://wn.com/Lecture_39_Multi_Dimensional_Scaling
To access the translated content:
1. The translated content of this course is available in regional languages. For details please visit https://nptel.ac.in/translation
The video course content can be accessed in the form of regional language text transcripts, books which can be accessed under downloads of each course, subtitles in the video and Video Text Track below the video.
Your feedback is highly appreciated. Kindly fill this form https://forms.gle/XFZhSnHsCLML2LXA6
2. Regional language subtitles available for this course
To watch the subtitles in regional languages:
1. Click on the lecture under Course Details.
2. Play the video.
3. Now click on the Settings icon and a list of features will display
4. From that select the option Subtitles/CC.
5. Now select the Language from the available languages to read the subtitle in the regional language.
- published: 10 Sep 2017
- views: 36185
15:34
Multidimensional Scaling: Classical Metric
Belajar Olah Data menggunakan Multidimensional Scaling: Classical Metric, dengan SPSS versi 22
Belajar Olah Data menggunakan Multidimensional Scaling: Classical Metric, dengan SPSS versi 22
https://wn.com/Multidimensional_Scaling_Classical_Metric
Belajar Olah Data menggunakan Multidimensional Scaling: Classical Metric, dengan SPSS versi 22
- published: 30 Nov 2024
- views: 3
30:12
Multidimensional Scaling (MDS) | Dimensionality Reduction Techniques (3/5)
To try everything Brilliant has to offer—free—for a full 30 days, visit https://brilliant.org/DeepFindr . The first 200 of you will get 20% off Brilliant’s annu...
To try everything Brilliant has to offer—free—for a full 30 days, visit https://brilliant.org/DeepFindr . The first 200 of you will get 20% off Brilliant’s annual premium subscription
▬▬ Papers / Resources ▬▬▬
Colab Notebook: https://colab.research.google.com/drive/1n_kdyXsA60djl-nTSUxLQTZuKcxkMA83?usp=sharing
Kruskal Paper 1964: http://cda.psych.uiuc.edu/psychometrika_highly_cited_articles/kruskal_1964a.pdf
Very old MDS Website: http://www.analytictech.com/borgatti/mds.htm
Rearrange Scalar Product:
- https://www.sjsu.edu/faculty/guangliang.chen/Math250/lec10mds.pdf
- https://github.com/drewwilimitis/Manifold-Learning/blob/master/Multidimensional_Scaling.ipynb
Metrics Blog Post: https://towardsdatascience.com/9-distance-measures-in-data-science-918109d069fa
Proof that MDS has no unique solution: https://github.com/drewwilimitis/Manifold-Learning/blob/master/Multidimensional_Scaling.ipynb
Best MDS Tutorials:
- https://www.jstatsoft.org/article/download/v073i08/1052
- https://rich-d-wilkinson.github.io/MATH3030/6-mds.html
- https://pages.mtu.edu/~shanem/psy5220/daily/Day16/MDS.html
- https://www.stat.pitt.edu/sungkyu/course/2221Fall13/lec8_mds_combined.pdf
- Past, Present & Future of MDS: https://repub.eur.nl/pub/39177/EI2013-07.pdf
- https://jessicastringham.net/2018/05/20/Multidimensional-Scaling/
- https://ccrma.stanford.edu/~unjung/mylec/mds.html
- https://github.com/drewwilimitis/Manifold-Learning/blob/master/Multidimensional_Scaling.ipynb
- http://cda.psych.uiuc.edu/mds_509_2013/borg_groenen/chapter_nine.pdf
- https://rstudio-pubs-static.s3.amazonaws.com/243040_fd2c3a25f33e48db994a01b517cbc341.html
Tübingen University Video:
https://www.youtube.com/watch?v=tJBVC2kzPCY&t=1340s&ab_channel=T%C3%BCbingenMachineLearning
Image Sources:
- https://www.researchgate.net/figure/36-sentiment-words-multidimensional-scaling-MDS-map-Reproduced-with-permission-from_fig2_333771792
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►E-Mail:
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▬▬ Used Music ▬▬▬▬▬▬▬▬▬▬▬
Music from #Uppbeat (free for Creators!):
https://uppbeat.io/t/sulyya/weather-compass
License code: ZRGIWRHMLMZMAHQI
▬▬ Used Icons ▬▬▬▬▬▬▬▬▬▬
All Icons are from flaticon: https://www.flaticon.com/authors/freepik
▬▬ Timestamps ▬▬▬▬▬▬▬▬▬▬▬
00:00 Introduction
00:36 Why learning old stuff?
01:19 Basics of MDS
02:26 Example from Psychometrics
03:50 Symmetry of Distance Matrix
04:17 Mathematical Framework
05:58 3 MDS Variants
07:20 Symbolic notations
07:45 Classical MDS (potentially boring)
12:31 Metric MDS
20:25 Brilliant.org Sponsoring
21:31 Code
25:20 Non-metric MDS
28:26 Summary Table
▬▬ My equipment 💻
- Microphone: https://amzn.to/3DVqB8H
- Microphone mount: https://amzn.to/3BWUcOJ
- Monitors: https://amzn.to/3G2Jjgr
- Monitor mount: https://amzn.to/3AWGIAY
- Height-adjustable table: https://amzn.to/3aUysXC
- Ergonomic chair: https://amzn.to/3phQg7r
- PC case: https://amzn.to/3jdlI2Y
- GPU: https://amzn.to/3AWyzwy
- Keyboard: https://amzn.to/2XskWHP
- Bluelight filter glasses: https://amzn.to/3pj0fK2
https://wn.com/Multidimensional_Scaling_(Mds)_|_Dimensionality_Reduction_Techniques_(3_5)
To try everything Brilliant has to offer—free—for a full 30 days, visit https://brilliant.org/DeepFindr . The first 200 of you will get 20% off Brilliant’s annual premium subscription
▬▬ Papers / Resources ▬▬▬
Colab Notebook: https://colab.research.google.com/drive/1n_kdyXsA60djl-nTSUxLQTZuKcxkMA83?usp=sharing
Kruskal Paper 1964: http://cda.psych.uiuc.edu/psychometrika_highly_cited_articles/kruskal_1964a.pdf
Very old MDS Website: http://www.analytictech.com/borgatti/mds.htm
Rearrange Scalar Product:
- https://www.sjsu.edu/faculty/guangliang.chen/Math250/lec10mds.pdf
- https://github.com/drewwilimitis/Manifold-Learning/blob/master/Multidimensional_Scaling.ipynb
Metrics Blog Post: https://towardsdatascience.com/9-distance-measures-in-data-science-918109d069fa
Proof that MDS has no unique solution: https://github.com/drewwilimitis/Manifold-Learning/blob/master/Multidimensional_Scaling.ipynb
Best MDS Tutorials:
- https://www.jstatsoft.org/article/download/v073i08/1052
- https://rich-d-wilkinson.github.io/MATH3030/6-mds.html
- https://pages.mtu.edu/~shanem/psy5220/daily/Day16/MDS.html
- https://www.stat.pitt.edu/sungkyu/course/2221Fall13/lec8_mds_combined.pdf
- Past, Present & Future of MDS: https://repub.eur.nl/pub/39177/EI2013-07.pdf
- https://jessicastringham.net/2018/05/20/Multidimensional-Scaling/
- https://ccrma.stanford.edu/~unjung/mylec/mds.html
- https://github.com/drewwilimitis/Manifold-Learning/blob/master/Multidimensional_Scaling.ipynb
- http://cda.psych.uiuc.edu/mds_509_2013/borg_groenen/chapter_nine.pdf
- https://rstudio-pubs-static.s3.amazonaws.com/243040_fd2c3a25f33e48db994a01b517cbc341.html
Tübingen University Video:
https://www.youtube.com/watch?v=tJBVC2kzPCY&t=1340s&ab_channel=T%C3%BCbingenMachineLearning
Image Sources:
- https://www.researchgate.net/figure/36-sentiment-words-multidimensional-scaling-MDS-map-Reproduced-with-permission-from_fig2_333771792
▬▬ Support me if you like 🌟
►Link to this channel: https://bit.ly/3zEqL1W
►Support me on Patreon: https://bit.ly/2Wed242
►Buy me a coffee on Ko-Fi: https://bit.ly/3kJYEdl
►E-Mail:
[email protected]
▬▬ Used Music ▬▬▬▬▬▬▬▬▬▬▬
Music from #Uppbeat (free for Creators!):
https://uppbeat.io/t/sulyya/weather-compass
License code: ZRGIWRHMLMZMAHQI
▬▬ Used Icons ▬▬▬▬▬▬▬▬▬▬
All Icons are from flaticon: https://www.flaticon.com/authors/freepik
▬▬ Timestamps ▬▬▬▬▬▬▬▬▬▬▬
00:00 Introduction
00:36 Why learning old stuff?
01:19 Basics of MDS
02:26 Example from Psychometrics
03:50 Symmetry of Distance Matrix
04:17 Mathematical Framework
05:58 3 MDS Variants
07:20 Symbolic notations
07:45 Classical MDS (potentially boring)
12:31 Metric MDS
20:25 Brilliant.org Sponsoring
21:31 Code
25:20 Non-metric MDS
28:26 Summary Table
▬▬ My equipment 💻
- Microphone: https://amzn.to/3DVqB8H
- Microphone mount: https://amzn.to/3BWUcOJ
- Monitors: https://amzn.to/3G2Jjgr
- Monitor mount: https://amzn.to/3AWGIAY
- Height-adjustable table: https://amzn.to/3aUysXC
- Ergonomic chair: https://amzn.to/3phQg7r
- PC case: https://amzn.to/3jdlI2Y
- GPU: https://amzn.to/3AWyzwy
- Keyboard: https://amzn.to/2XskWHP
- Bluelight filter glasses: https://amzn.to/3pj0fK2
- published: 16 Jan 2024
- views: 6596