Topic: "percentile-method"
zuhaib1214/Feature-Engineering
This repository is totally focused on Feature Engineering Concepts in detail, I hope you'll find it helpful.
Language: Jupyter Notebook - Size: 15.9 MB - Last synced at: almost 2 years ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0
aneeshmurali-n/ML_Bangalore_House_Price_Analysis
This project focusing on statistical analysis to understand and prepare data for potential machine learning applications. The dataset house_price.csv includes property prices in Bangalore. The analysis aims to perform exploratory data analysis (EDA), detect and handle outliers, check data distribution and normality, and analyze correlations.
Language: Jupyter Notebook - Size: 4.25 MB - Last synced at: about 2 months ago - Pushed at: 9 months ago - Stars: 1 - Forks: 0
Khushi130404/Outlier_Exterminator
Outlier_Exterminator is a Python tool for detecting and treating outliers using IQR, Z-Score, and Percentile methods. It supports trimming, capping, and Winsorization, demonstrated in a Jupyter Notebook.
Language: Jupyter Notebook - Size: 455 KB - Last synced at: 3 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0
nani757/Outlier-Detection-and-Removal
An outlier is a data point that is noticeably different from the rest. They represent errors in measurement, bad data collection, or simply show variables not considered when collecting the data.An outlier is a data point that is noticeably different from the rest. They represent errors in measurement, bad data collection, or simply show variables not considered when collecting the data.
Language: Jupyter Notebook - Size: 367 KB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 0 - Forks: 0
