This repository explores various techniques for handling categorical variables in data preprocessing, focusing on methods such as one-hot encoding, label encoding, and their applications in machine learning models.

vtreat is a data frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. Distributed under choice of GPL-2 or GPL-3 license.

Source Code for Paper "Improving survey inference using administrative records without releasing individual-level continuous data"

Data Science Foundations I | Exploratory Data Analysis in Python | Summarizing Relationship Between Two Features

ANOVA_diamonds_analysis

Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadri. Collaborators welcome.

A function to run Bhapkar's test from Bhapkar (1968) 'On the analysis of contingency tables with a quantitative response' Biometrics, 24 (2): 329-38.

Fast Estimation of Linear Models with IV and High Dimensional Categorical Variables

This package provides functions to create descriptive statistics tables for continuous and categorical variables.

This code demonstrates the basic end-to-end workflow of developing, training, and evaluating a deep artificial neural network classifier on a real-world classification problem involving preprocessing of categorical variables.

A Deep Learning Project on "IMAGE DETECTION" using MNIST and FASHION MNIST datasets. We will be using many combinations of activation fucntions, loss and other normalization techniques to show how the accuracy improves if certain parameters are added to the netwrok and many such implementations.

Dealing with categorial data: CATCODE simple fuction to label encoding with Excel

CUHK Course code: STAT 3011 | This course is designed to strengthen students' ability in statistical computing as well as in processing and analysing data. Students are required to participate in several term projects with emphasis on techniques of data management and analysis.

How to deal with Missing Values, Categorical Variables, Pipelines, Cross-Validation, XGBoost, Data Leakage

Implementation of Naive Bayes algorithm for categorical data

A list of python notebooks for Machine learning basics- regression and classification.

Types of Variables in Research: Numeric/Quantitative vs Categorical

This python code shows howw regression is handled in case of categorical variables using duumies. It calculates the multiple regression code and shows the regression table. It also performs the residual analysis.

A library for the hyperparameter optimization of deep neural networks