A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
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Updated
May 9, 2024 - Python
A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].
RADseq Data Exploration, Manipulation and Visualization using R
Fifteen observations of the vertical semidiameter of Venus, made by Lieutenant Herndon, with the meridian circle at Washington, in the year 1846.
🔗 Methods for Correlation Analysis
To perform exploratory data analysis and visualization on a dataset containing customer information, to identify potential target customers for the bank’s future marketing campaign.
ELKI Data Mining Toolkit
pca: A Python Package for Principal Component Analysis.
Labeled wireless sensor network data set collected from a multi-hop wireless sensor network deployment using TelosB motes.
Labeled wireless sensor network data set collected from a simple single-hop wireless sensor network deployment using TelosB motes.
Contains R codes for processing and analyzing data for Great Lakes Cladophora work
RoBTT R package for estimating robust Bayesian t-test
This repository houses an interactive flex dashboard on outlier analysis. It accompanies a presentation on the same topic.
A speed dating analysis
Exploratory Data Analysis (EDA) on a dataset from Kaggle
This is an example of data cleaning, this project uses Jupiter Notebook and Python
Assignment Advance Stats
Content: Eliminating Outliers using Boxplot, Checking correlation using Scatter plot & Heat map, Types of Correlation, EDA, Data preprocessing
🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams
Dixon's Q Test calculator package for Dart
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