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GitHub topics: target-encoding

sadpepep/ML_preprocessing

Data preprocessing for machine learning modelling. Quantile transformation for the outliers removal, replacing NULLs with medians, using target encoder and Z-score standardisation for the numeric variables.

Language: Jupyter Notebook - Size: 2.53 MB - Last synced at: 10 months ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

johannaschmidle/House-Price-Predictor

A machine learning model to accurately predict house prices based on various features such as quality, size, and location, utilizing Random Forest and XGBoost algorithms (Python)

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vla6/Blog_gnn_naics

Exploring categorical features with various encodings and models

Language: Jupyter Notebook - Size: 66.1 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 4 - Forks: 0

NaquibAlam/M5_Forecasting_Accuracy_kaggle

It contains the code and data for M5 Forecasting - Accuracy competition on Kaggle.

Language: Jupyter Notebook - Size: 9.69 MB - Last synced at: about 1 year ago - Pushed at: over 4 years ago - Stars: 4 - Forks: 0

VipinindKumar/Predict-Future-Sales

Deployed model to predict total sales for every item and shop for the next month, from a time-series dataset consisting of daily sales data

Language: Jupyter Notebook - Size: 1.96 MB - Last synced at: about 1 year ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 1

rafah91/life-expectancy-data-processing

Life expectancy data processing

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sharmaroshan/Fraud-Detection-in-Insurace-Claims

This is a very Important part of Data Science Case Study because Detecting Frauds and Analyzing their Behaviours and finding reasons behind them is one of the prime responsibilities of a Data Scientist. This is the Branch which comes under Anamoly Detection.

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sharmaroshan/Christiano-Ronaldo---Goal-Prediction-Top-40-

It is a Problem Which I got During the ZS Data Science Challenge From Interview Bit Hiring Challenge Where I secured a 40th Rank out of 10,000 Students across India. It is a Dataset which requires Intensive Cleaning and Processing. Here I have Performed Classification Using Random Forest Classifier and Used Hyper Tuning of the Parameters to achieve the Accuracy. I got a very Satisfiable Accuracy from the Model in both the Training and Testing Sets.

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Nikolay-Lysenko/dsawl πŸ“¦

A set of tools for machine learning (for the current day, there are active learning utilities and implementations of some stacking-based techniques).

Language: Python - Size: 194 KB - Last synced at: 4 days ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 0

mustafahakkoz/Advertisement-CTR-Prediction

A submission for HUAWEI - 2020 DIGIX GLOBAL AI CHALLENGE

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schatzederwelt/stock-prices-cars

ΠŸΡ€ΠΎΠ³Π½ΠΎΠ·ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ Ρ€Ρ‹Π½ΠΎΡ‡Π½ΠΎΠΉ стоимости Π°Π²Ρ‚ΠΎΠΌΠΎΠ±ΠΈΠ»Π΅ΠΉ

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toan01-uet/Solution-for-HackerEarth-Machine-Learning-challenge

HackerEarth Machine Learning challenge: Of Genomes And Genetics

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NaquibAlam/Categorical_Encoding_Experimentation

This repo contains code for experimenting with categorical encoding - WoE, Catboost, Target encoder, and many more.

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ShrishailSGajbhar/Coursera-Project

Final project for "How to win a data science competition" Coursera course

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vanshika97/ML_IncomePrediction

TCD ML Comp. 2019/20 - Income Prediction (Ind.)

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paritoshkc/Income_predictor

Language: Python - Size: 639 KB - Last synced at: over 2 years ago - Pushed at: over 5 years ago - Stars: 0 - Forks: 0

Related Keywords
target-encoding 16 machine-learning 7 python 5 random-forest 4 data-analysis 3 feature-engineering 3 linear-regression 2 data-science 2 categorical-data 2 python3 2 data-visualization 2 data-cleaning 2 time-series 2 lightgbm 2 jupyter-notebook 2 kaggle 2 xgboost 2 cross-validation 2 sklearn 2 ordinal-encoding 2 ctr-prediction 1 mini-batch-gradient-descent 1 out-of-core 1 imbalanced-classification 1 sgd-classifier 1 hackerearth-solutions 1 unbalanced-data 1 automl 1 column-transformer 1 regression 1 randomized-search 1 feature-importance 1 make-pipeline 1 pandas 1 ohe-encoding 1 catboost 1 xgboost-python 1 trinity-college-dublin 1 rmse-score 1 polynomial-regression 1 outliers 1 income-prediction 1 kaggle-solution 1 kaggle-dataset 1 kaggle-competition 1 gradientboosting 1 coursera-course 1 coursera 1 high-cardinality-encoding 1 categorical-encoding 1 smote-oversampler 1 mutilabelclassification 1 machinelearningchallenge 1 labelencoding 1 class-weights 1 feature-selection 1 e-commerce 1 deployment 1 m5-forecasting 1 groupkfold-cv 1 neural-network 1 embeddings 1 deep-graph-infomax 1 xgboost-model 1 visualization 1 sklearn-library 1 random-forest-regressors 1 onehot-encoding 1 house-price-prediction 1 anova-test 1 z-score-normalization 1 quantile-transformer 1 stacking 1 out-of-fold 1 epsilon-greedy 1 categorical-features 1 active-learning 1 profiling 1 predicting-missing-values 1 parameter-tuning 1 classification 1 imblearn 1 imbalanced-learning 1 imbalanced-data 1 balanced-random-forest 1 one-hot-encoding 1 label-encoder 1 hyperparameter-tuning 1 heroku 1