Similar image retrieval using distance measure coded in MATLAB

A statistical analysis of Indian movies data set.

In statistics, an outlier is an observation point that is distant from other observations. How we can filter out these values using python?

Machine Learning Nano-degree Project : To identify customer segments hidden in product spending data collected for customers of a wholesale distributor

A outlier removal tool, removes outlier row-wise using z-score or InterQuartile Range method

1-Outlier detection and removal of the outlier by Using IQR The Data points consider outliers if it's below the first quartile or above the third quartile 2-Remove the Outliers by using the percentile 3-Remove the outliers by using zscore and standard deviation

I have used Boston Housing Dataset, which is available at Sklearn API. Find out the outliers using box plot, scatter plot and clean them using Z score and IQR method.

The following data are numbers of passengers on flights of Delta Air Lines between San Francisco and Seattle over 33 days in April and early May. 128, 121, 134, 136, 136, 118, 123, 109, 120, 116, 125, 128, 121, 129, 130, 131, 127, 119, 114, 134, 110, 136, 134, 125, 128, 123, 128, 133, 132, 136, 134, 129, 132

The following data are annualized returns on a group of 15 stocks. 12.5, 13, 14.8, 11, 16.7, 9, 8.3, -1.2, 3.9, 15.5, 16.2, 18, 11.6, 10, 9.5

Following are the numbers of daily bids received by the government of a developing country from firms interested in winning a contract for the construction of a new port facility

Data: 23, 26, 29, 30, 32, 34, 37, 45, 57, 80, 102, 147, 210, 355, 782, 1209

Solution to Aczel problems practice (1-74, 1-75)

Data Mining and Machine Learning APS Failure at Scania Trucks Data Set.

Box Plot - using dataframe in pandas Inserting Minor and Major gridlines Deriving LQ, UQ, IQR, Upper Whisker and Lower Whisker length

Premise of Task: Contextual Alert and Trend System (CATS) is a proof of concept (POC) for an automated system for near real-time media monitoring via GDELT to identify trends and anomalies in the volume of online reports about pre-defined indicator events, at country level. This repository reflects the methodologies used to complete this task.

Data analysis and outliers detection of air quality data.

demir.ai Dataset Operations

A machine learning project where we first detected and removed the outliers and then checked correlation among features and then applied different ML algorithms to check if the person might get a heart attack or not.

This repository contains the source code for Statistics.JS.

Description of outliers