categorical

Plot categorical heatmaps with seaborn

Perform a chi-square independence test.

Keras, Tensorflow eager execution implementation of Categorical Variational Autoencoder

A python package for plotting Evidence Gap Maps using Plotly

A simple preprocessing method for Machine Learning

Quasi-determinism screening for fast Bayesian Network Structure Learning (from T.Rahier's PhD thesis, 2018)

Associated to SAMO paper

Jupyter notebooks on custom loss functions in TensorFlow/Keras: modified MSE penalizing overconfidence and Categorical Focal Loss with L1/L2 regularization for imbalanced multi-class tasks (e.g., cats_vs_dogs). Includes model building, preprocessing, GPU checks, and focuses on learning mechanics over metrics.

WF16 federation gateway for mo:os kernels — URN-prefix shard routing. Go, stdlib-first.

Categorical hypergraph rewriting kernel — semantic functorial network over distributed compute. Go, stdlib-first.

This repository contains small MATLAB scripts that I’ve used, tested, and even tweaked for spatial analysis. These scripts cover everything from categorical statistics to statistical trends for each pixel. Feel free to download them and use them on your local machine. I’d love to hear how you like them!

Visualize gender-based employment status and recruitment sources using stacked bar plots in Python.

ML project template created while following the Abhishek Thakur's youtube video

Data on Youtube trending videos , cleaning and EDA

Extensions and additions to vcd: Visualizing Categorical Data

Fun Project -: Playing with the statistics. Main Motto -: Trying to understand the statistics underneath the various most commonly used Machine Learning Models. I have used two library i.e. Stats-Model and Scikit-Learn.

EDA / Data Visualization of Hotstar Shows

Sufficient Representation for Categorical Variables https://arxiv.org/abs/1908.09874v1

Titanic Survival Prediction Using Decision Tree. This project uses a Decision Tree Classifier to predict Titanic passenger survival based on the Kaggle dataset. It covers data preprocessing, feature engineering, and model training with Scikit-learn.

The following codes were used to conduct Confirmatory Factor Analysis and Structural Equation Modeling in R, and Multiple Group Analysis in R for my thesis entitled "Analysing DASS through Structural Equation Modeling". Note: THE DATA USED IS NOT MY OWN AND WAS OBTAINED FROM Open-Source Psychometrics Project (https://fhssrsc.byu.edu/r-works)