Categorial and numerical (ordinal and nonordinal) Data Clustering Algorithm
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Updated
May 18, 2024 - Python
Categorial and numerical (ordinal and nonordinal) Data Clustering Algorithm
Scikit-klearn compatible BinaryEncoder class capable of handling unseen categories in an automated fashion
Implementation of the Entity Embedding Encoder
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.
Importing Dataset, missing data,
Kaggle Titanic Competition
A simplified algorithm to cluster mixed-type data(numerical and categorical).
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
FuzzykCenters algorithms for fuzzy clustering categorical data
Python package to perform mixed-type distance calculations
Category transformation
Interpretable Deep Classification of Categorical Data
using ML to predict who lives and dies in titantic disaster
🔥[IEEE TPAMI 2023] Official repository TPAMI 2023 paper "Exploiting Field Dependencies for Learning on Categorical Data"
This repository contains the project of Hepatitis C Prediction by Machine Learning.
Using ML to predict house price
🌲 Decision Trees in scikit-learn with categorical and numerical data.
Categorical image classification of images using MNIST handwritten digit dataset, TensorFlow and Keras.
This is a classification exercise which uses categorical data and weighted entropy to determine the dependent variable.
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