Scikit-klearn compatible BinaryEncoder class capable of handling unseen categories in an automated fashion
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Updated
Sep 28, 2018 - Python
Scikit-klearn compatible BinaryEncoder class capable of handling unseen categories in an automated fashion
Implementation of the Entity Embedding Encoder
A simplified algorithm to cluster mixed-type data(numerical and categorical).
Kaggle Titanic Competition
A basic collection of statistical tools for measuring categorical correlation
FuzzykCenters algorithms for fuzzy clustering categorical data
Interpretable Deep Classification of Categorical Data
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🌲 Decision Trees in scikit-learn with categorical and numerical data.
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This is a classification exercise which uses categorical data and weighted entropy to determine the dependent variable.
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
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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.
This project is about building a artificial neural network using pytorch library. I am sharing the code and output for my project.
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