Alternatives and similar repositories for kaggle-advanced-regression-algos:

Users that are interested in kaggle-advanced-regression-algos are comparing it to the libraries listed below

• PacktPublishing / Ensemble-Machine-Learning
  Code repository for Ensemble Machine Learning, published by Packt
  ☆48Updated 4 years ago
• jingmin1987 / variable-clustering
  A re-creation of SAS varclus procedure in Python
  ☆23Updated 6 years ago
• zhulei227 / Stacking_Ensembles
  Stacking classification and regression
  ☆22Updated 5 years ago
• tomonori-masui / time-series-forecasting
  Multi-step Time Series Forecasting with ARIMA, LightGBM, and Prophet
  ☆24Updated 3 months ago
• KSpiliop / Fraud_Detection
  Tuning XGBoost hyper-parameters with Simulated Annealing
  ☆52Updated 7 years ago
• alianoroozi / Cost-Sensitive-Learning-By-Genetic
  A python implementation of a genetic algorithm based approach for cost sensitive learning
  ☆8Updated 5 years ago
• radicali94 / TimeSeries-Regression
  Comparing XGBoost, CatBoost and LightGBM on TimeSeries Regression (RMSE, R2, AIC) on two different TimeSeries datasets.
  ☆22Updated 5 years ago
• IBM / xgboost-smote-detect-fraud
  Can we predict accurately on the skewed data? What are the sampling techniques that can be used. Which models/techniques can be used in t…
  ☆64Updated 4 years ago
• mldataanalysis / Dealing-With-Imbalanced-Data
  Using Imblearn To Tackle Imbalanced Data Sets
  ☆37Updated 8 years ago
• carloschavez9 / ensemble-time-series
  Ensemble Machine Learning for Time Series: Ensemble of Deep Recurrent Neural Networks and Random forest using a Stacking (averaging) laye…
  ☆35Updated 7 years ago
• msahamed / handle_imabalnce_class
  Address imbalance classes in machine learning projects.
  ☆65Updated 6 years ago
• weepon / feature_selection
  常用的特征选择方法
  ☆68Updated 2 years ago
• louis925 / kaggle-web-traffic-time-series-forecasting
  Solution to Kaggle - Web Traffic Time Series Forecasting
  ☆35Updated 5 years ago
• xuman-Amy / preprocessing
  数据预处理之缺失值处理，特征选择
  ☆21Updated 5 years ago
• bits-bytes-nn / mofc-demand-forecast
  Time Series Forecasting for the M5 Competition
  ☆40Updated 3 years ago
• KunalArora / kaggle-m5-forecasting
  Time-Series forecasting using Stats models, LightGBM & LSTM
  ☆37Updated 4 years ago
• effa / time-series-clustering
  Project for PV056 Machine learning course on clustering of time series
  ☆22Updated 7 years ago
• yanshanjing / learning-from-imbalanced-classes
  Learning From Imbalanced Classes
  ☆12Updated 8 years ago
• sjtupig / MissingImputer
  use knn, randomforest, xgboost, lightgbm to fill missing values
  ☆14Updated 6 years ago
• farshidrayhancv / CUSBoost
  ☆22Updated 5 years ago
• SantiagoEG / FCBF_module
  Fast Correlation-Based Feature Selection
  ☆31Updated 7 years ago
• nnikolaou / Cost-sensitive-Boosting-Tutorial
  Tutorial on cost-sensitive boosting and calibrated AdaMEC.
  ☆26Updated 7 years ago
• huidudaozou / Time-Series
  《应用时间序列分析》易丹辉、王燕著； 案例Python实现
  ☆16Updated 5 years ago
• CcIsHandsome / -TOP1-
  CCF大数据与计算智能大赛-工件检测TOP1方案
  ☆27Updated 5 years ago
• tlatkowski / tf-feature-selection
  Implementation of various feature selection methods using TensorFlow library.
  ☆9Updated 2 years ago
• HanXiaoyang / Feature_Engineering_and_XGBoost_Parameter_Tuning
  Examples of how to do feature engineering and Xgboost parameter tuning
  ☆46Updated 8 years ago
• aflyingpig0226 / feature-engineering
  机器学习的特征工程，包括特征抽取、特征预处理、特征选择、特征降维。
  ☆25Updated 6 years ago
• manujosephv / deeprenewalprocess
  GluonTS Implementation of Intermittent Demand Forecasting with Deep Renewal Processes arXiv:1911.10416v1 [cs.LG]
  ☆31Updated 3 years ago
• OpenIDEA-YunanUniversity / ycimpute
  A missing value imputation library based on machine learning. It's implementation missForest, simple edition of MICE(R pacakge), knn, EM,…
  ☆106Updated last year
• Albertsr / Machine-Learning
  LR / SVM / XGBoost / RandomForest etc.
  ☆28Updated 4 years ago