categorical-encoding

There are 0 repository under categorical-encoding topic.

cpa-analytics / embedding-encoder
Scikit-Learn compatible transformer that turns categorical variables into dense entity embeddings.
machine-learning deep-learning scikit-learn keras tensorflow neural-networks categorical-features categorical-encoding embeddings
Language:Jupyter Notebook 40
leffff / waveml
Open source machine learning library with various machine learning tools
stacked-predictions linear-transformations weighted-averages stacking ensemble categorical-encoding feature-transformation
Language:Python 12
albertusk95 / weight-of-evidence-spark
Weight of Evidence Encoding & Information Value
categorical-encoding information-value machine-learning weight-of-evidence
Language:Python 9
arunsinghbabal / Controlled-Automation-for-Data-Processing
Perform semi automated exploratory data analysis, feature engineering and feature selection on provided dataset by visualizing every possibilities on each step and assisting the user to make a meaningful decision to achieve a low-bias and low-variance model.
data-science data-visualization exploratory-data-analysis feature-engineering feature-selection machine-learning python categorical-encoding data-transformation auto-eda auto-feature-engineering auto-feature-selection
Language:Jupyter Notebook 5
AshiniAnantharaman / Image_classification_of_CIFAR10_dataset
The project uses Artificial Neural Network and Convolutional Neural Network to classify images into 10 different categories.
artificial-neural-networks categorical-encoding classification confusion-matrix convolutional-neural-networks sklearn-library tensorflow
Language:Jupyter Notebook 0
ecvsgl / MLproject-DrivenData-PumpItUp
Exploratory data analysis and model preparation for DrivenData contest: PumpItUp!
categorical-encoding classification-model drivendata exploratory-data-analysis gradient-boosting-classifier knn-classification logistic-regression machine-learning numpy pandas random-forest scikit-learn xgboost
Language:Jupyter Notebook 0
gshashank84 / ResponseEncoding
Encode Categorical Features based on Target/Class
response-encoding encoding target-encoding categorical-encoding categorical-features categorical-variables
Language:Python 0
IvanSaravanja2306 / Machine_Learning_Models
Machine Learning Models
anova categorical-encoding data-encoding decision-tree-classifier dimensionality-reduction exploratory-data-analysis knn-classification logistic-regression ordinal-encoding pca random-forest support-vector-machines t-test
Language:Jupyter Notebook 0
Yashasvi863 / Machine-Learning-Classification
Customer Churn Analysis
categorical-encoding confusion-matrix feature-extraction feature-selection gridsearchcv logistic-regression random-forest xgboost
Language:Jupyter Notebook 0
dixitamol / ML_code_templates_R
Code templates for different ML algorithms
ann apriori-algorithm association-rules backwardpropagation categorical-encoding classification clustering crossvalidation decision-trees eclat-algorithm forward-selection lda naive-bayes-classifier nlp pca regression reinforcement-learning svm upper-confidence-bounds xgboost
Language:R
ejaj / stacked-classifier
Stacked Classifier
categorical-encoding data-exploration data-processing data-visualization feature-engineering feature-scaling machine-learning multilayer-perceptron random-forest support-vector-machines
Language:Jupyter Notebook
MylieMudaliyar / Feature-Engineering-Techiques-on-House-Values
The feature engineering techniques discussed are - dimensionality reduction(pca), scaling(standard scaler, normalizer, minmaxscaler), categorical encoding(one hot/dummy), binning, clustering, feature selection. These are techniques performed on a dataset consisting of Californian House Prices.
binning categorical-encoding dimensionality-reduction feature-engineering kmeans-clustering linear-regression mean-absolute-error minmaxscaler normalizer one-hot-encoding pca python random-forest-regressor standardscaler
Language:Jupyter Notebook
NaquibAlam / Categorical_Encoding_Experimentation
This repo contains code for experimenting with categorical encoding - WoE, Catboost, Target encoder, and many more.
categorical-encoding target-encoding high-cardinality-encoding
NavindaFernando / Feature-Extraction
Heart Risk Level Predicting Regression Model & Web using Feature Engineering and Data Preprocessing :baby_chick:
categorical-encoding feature-engineering flask handling-outlier joblib numpy pandas polynomial-features scaling label-encoding quantile-transformer machine-learning html5
Language:Jupyter Notebook
SayamAlt / E-Commerce-Text-Classification
Successfully established a machine learning model that can accurately classify an e-commerce product into one of four categories, namely "Books", "Clothing & Accessories", "Household" and "Electronics", based on the product's description.
categorical-encoding cross-validation exploratory-data-analysis hyperparameter-optimization machine-learning model-deployment model-training-and-evaluation text-classification text-preprocessing text-vectorization
Language:Jupyter Notebook
subhayuroy / KickStarter
🎬This KickStarter project is about some🎞 foreign films🎥 and music videos🎶. This is an analysis 📽of their 'goal currency' and release time.🎦
baseline-model categorical-encoding feature-generation feature-selection feature-engineering
Language:Jupyter Notebook
venkat-a / Text_Processing_RNN_LSTM
Text Processing RNN leverages RNN and LSTM models for advanced text processing. It features deep learning techniques for NLP tasks, utilizing GloVe for word embeddings, aimed at both educational and practical applications.
model-evaluation-and-tuning categorical-encoding deep-neural-networks embedding-vectors lstm-neural-networks nltk-tokenizer numpy-arrays pandas-dataframe pytorch-nlp rnn-encoder-decoder tokenization vocabulary-builder
Language:Jupyter Notebook