Alternatives and similar repositories for machine-learning

Users that are interested in machine-learning are comparing it to the libraries listed below

• luanshiyinyang / Stacking
  机器学习集成模型之Stacking各类模型及工具源码
  ☆121Updated 5 years ago
• Ultraopxt / Predict-the-rent-probability-of-a-room
  机器学习预测模型，分别用逻辑回归，决策树，随机森林，神经网络，XGBOOST和支持向量机算法建模，交叉验证，并选出AUC最优的模型。特征工程优化后，AUC值达到0.8259
  ☆58Updated 5 years ago
• ShaoQiBNU / stacking
  集成学习Stacking方法详解
  ☆82Updated 6 years ago
• wikke / TimeSeriesPrediction
  Time Series Prediction, Stateful LSTM; 时间序列预测，洗发水销量/股票走势预测，有状态循环神经网络
  ☆56Updated 8 years ago
• Alxe1 / FeatureSelectionsAndExtractions
  feature selections and extractions
  ☆88Updated last year
• coder23263 / Machine_learning_prediction_system
  机器学习预测系统汇总：包括贝叶斯网络、马尔科夫模型、线性回归、岭回归、多项式回归、决策树回归、深度神经网络预测
  ☆90Updated 5 years ago
• angeliababy / houseprice_regression
  数据特征工程、各种机器学习回归模型、回归数据预处理
  ☆43Updated 6 years ago
• AbtMyML / -SVM
  麻雀算法优化支持向量机 python实现
  ☆15Updated 3 years ago
• L-ear / RandomForest
  python实现的随机森林
  ☆112Updated 3 years ago
• rogeroyer / feature_selection_GAAlgorithm
  基于遗传算法的特征选择
  ☆127Updated 6 years ago
• HiddenSharp / LSTM-SVM-RF-time-series
  Regression prediction of time series data using LSTM, SVM and random forest. 使用LSTM、SVM、随机森林对时间序列数据进行回归预测，注释拉满。
  ☆200Updated 5 years ago
• slydg / GRU_to_predict_timeseries
  使用pytorch搭建的循环神经网络在股票数据时间序列上的应用
  ☆109Updated 7 years ago
• SMU-Rainflow / PM2.5_predict
  XGB、LSTM、KNNR、SVR预测
  ☆13Updated last year
• cxdsz / stock-price-prediction-algorithms
  使用随机森林、bp神经网络、LSTM神经网络、GRU对股票收盘价进行回归预测。Random forest, BP neural network, LSTM neural network and GRU are used to predict the closing pric…
  ☆52Updated 5 years ago
• tjaume / BPNeuralNetworks
  利用Python实现三层BP神经网络
  ☆84Updated 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
  ☆17Updated 6 years ago
• hellobilllee / lstm_stock_price_prediction
  LSTM神经网络预测沪深300指数及其涨跌
  ☆44Updated 5 years ago
• MaybeWilliam / stock-price-prediction-BPNN-LSTM
  Use BPNN and LSTM to forecast stock price. 使用BP神经网络和LSTM预测股票价格，注释拉满。
  ☆208Updated 3 years ago
• weepon / feature_selection
  常用的特征选择方法
  ☆67Updated 3 years ago
• jia-zhuang / xgboost-lightgbm-hyperparameter-tuning
  Bayesian Optimization and Grid Search for xgboost/lightgbm
  ☆79Updated 11 months ago
• anmoltigga / GA-LSTM
  Python notebook implementation of hyperparameter tuning of LSTM deep learning model using Genetic algorithm
  ☆22Updated 4 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
• Timecollector / Grey_Model
  包含灰色预测模型：灰色单变量预测模型GM(1,1)模型，灰色多变量预测模型GM(1,N)模型，GM(1,N)幂模型，灰色多变量周期幂模型GM(1,N|sin)幂模型，以及灰色关联模型
  ☆82Updated 3 years ago
• ccc-hhh / BPNN-regression-and-classify
  1、BP-momentum神经网络numpy实现及Pytorch实现及各optim在AQI数据集的表现。2、BP网络分类
  ☆41Updated 5 years ago
• Wddzht / DataPreprocessing
  数据预处理过程(属性选择, 异常值处理, 归一化, 标准化等)
  ☆66Updated 5 years ago
• ymzx / pso-svm
  粒子群算法优化支持向量机
  ☆143Updated 3 years ago
• bingdiaoxiaomao / hyper-parameters-optimization
  机器学习算法超参数的优化方法——基于hyperopt和bayes_opt
  ☆14Updated 7 years ago
• FuSiry / Nirs-Pls-Corn
  This code is a near-infrared spectrum modeling method based on PCA and pls
  ☆34Updated 4 years ago
• shiluqiang / GBDT_regression
  GBDT for regression
  ☆10Updated 7 years ago
• oubahe / GSA-PSO-SVR
  一种有效的电力负荷预测方法
  ☆64Updated 6 years ago