categorical-features
There are 60 repositories under categorical-features topic.
catboost/catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
serengil/chefboost
A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical features support for Python
Atomu2014/product-nets
Tensorflow implementation of Product-based Neural Networks. An extended version is at https://github.com/Atomu2014/product-nets-distributed.
mmortazavi/EntityEmbedding-Working_Example
This repository contains a notebook demonstrating a practical implementation of the so-called Entity Embedding for Encoding Categorical Features for Training a Neural Network.
cpa-analytics/embedding-encoder
Scikit-Learn compatible transformer that turns categorical variables into dense entity embeddings.
bfgray3/cattonum
Encode Categorical Features (unmaintained)
konodyuk/kts
Interactive ML Toolset
vc1492a/henosis
A Python framework for deploying recommendation models for form fields.
davidmasse/US-supreme-court-prediction
Predicting the ideological direction of Supreme Court decisions: ensemble vs. unified case-based model
adimajo/glmdisc_python
glmdisc Python package: discretization, factor level grouping, interaction discovery for logistic regression
bhattbhavesh91/catboost-tutorial
A small tutorial to demonstrate the power of CatBoost Algorithm
c4pub/deodel
A mixed attributes predictive algorithm implemented in Python.
licesonw/deepmm
Multimodal deep learning package that uses both categorical and text-based features in a single deep architecture for regression and binary classification use cases.
raynardj/category
Category transformation
abhmalik/categorical-feature-importances-without-one-hot-encoding-dummies
Feature Importance of categorical variables by converting them into dummy variables (One-hot-encoding) can skewed or hard to interpret results. Here I present a method to get around this problem using H2O.
Kunal1198/Customer-Category-Prediction-ML
Supervised Learning Problem. In this categorizing the customers in four groups, as follows: 1- Basic Service 2- E-Service 3- Plus Service 4- Total Service.
Nikolay-Lysenko/dsawl
A set of tools for machine learning (for the current day, there are active learning utilities and implementations of some stacking-based techniques).
ocramz/record-encode
Generic encoding of record types
viktorsapozhok/cafeen
Kaggle Categorical Feature Encoding Challenge II, private score 0.78795 (110 place)
alvimahmud-osu/Kaggle-Cat-in-the-hat-ii
Kaggle Competition (Encoding categorical variables)
Ansu-John/Natural-Language-Processing
Explore various natural language processing models using Python.
ItsWajdy/categorical_features_euclidean_distance
A python package to compute pairwise Euclidean distances on datasets with categorical features in little time
Maskar/chicago_traffic_crashes
This study creates machine learning models to predict the seriousness of car crashes using 2019 and 2020 crash reports from the publicly accessable database maintained by the Chicago Police Department. A car crash is considered serious if the crash results in an injury or the car is towed due to the crash. Models use categorical features that describe conditions at the time of the crash and crash causes to predict the required target. The current focus is to classify whether a crash results in an injury. All machine learning models are trained, validated, and tested on randomly split 2019 crash reports. The best model (along with all others) are then tested using the full set of 2020 crash reports.
Navadeeppasala/Data-Analysis-with-Python
Why data analysis? , How to understand the problem, what to do for data analysis, and how clean the data for building Machine Learning models
praxitelisk/CATegorical-Feature-Encoding-Challenge
Binary classification, with every feature as categoricals
victor7246/Notebooks
This repository contains notebooks on different topics across - linear algebra, image classification, language models etc.
ahmedlrashed/housing-prediction-model
Built and optimized a predictive regression model of housing prices with historical CA housing data.
jessislearning/Medical-Data-Visualizer
Data Analysis with Python project from freeCodeCamp (3 of 5)
ShrayanRoy/cda_project
Project of a coursework - Categorical Data Analysis (M.Stat Semester 2) under the supervision of Prof. Arindam Chatterjee.,ISID
marcello-calabrese/edatemplates
Exploratory Data Analysis standard templated in markdown and txt format
PriyankaSett/obesity_multiclassification
Given a person's data, the task is to predict that in which category the person's weight should fit in. This is a Multiclassification project.