Efficient matrix representations for working with tabular data
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Updated
May 13, 2024 - Python
Efficient matrix representations for working with tabular data
Discover relevant information about categorical data with entity embeddings using Neural Networks (powered by Keras)
Naive Bayes with support for categorical and continuous data
Embed categorical variables via neural networks.
Bayesian entropy estimation in Python - via the Nemenman-Schafee-Bialek algorithm
Outlier detection for categorical data
Solution to Kaggle's Mercari Price Suggestion Competition
Machine Learning/Pattern Recognition Models to analyze and predict if a client will subscribe for a term deposit given his/her marketing campaign related data
A mixed attributes predictive algorithm implemented in Python.
Categorial and numerical (ordinal and nonordinal) Data Clustering Algorithm
Category transformation
🔥[IEEE TPAMI 2023] Official repository TPAMI 2023 paper "Exploiting Field Dependencies for Learning on Categorical Data"
This project is about building a artificial neural network using pytorch library. I am sharing the code and output for my project.
A small library that can encode categorical variables to entity embeddings using a TensorFlow 2.0 neural network. Supports classification and regression problems. Network parameters are adjustable.
The convenient loan experience, however, has to be balanced against the fact that the company does charge an origination fee. This is a case study for a company that wants a model developed which will help the agents to visit the right customer looking at the prediction that the model would make depending on the given data fields.
Prepare a classification model using Naive Bayes for salary data
Importing Dataset, missing data,
Python package to perform mixed-type distance calculations
This repository contains the project of Hepatitis C Prediction by Machine Learning.
A supervised autoencoder and its GUI for cost-less thyroid nodule prognosis.
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