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Search results for python cross validation

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36 search results found

Iterative Stratification ⭐ 650

scikit-learn cross validators for iterative stratification of multilabel data

Time Series Cross-Validation -- an extension for scikit-learn

Automl_alex ⭐ 171

State-of-the art Automated Machine Learning python library for Tabular Data

Hcrystalball ⭐ 135

A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.

Autoreject ⭐ 132

Automated rejection and repair of bad trials/sensors in M/EEG

Neuropredict ⭐ 99

Easy and comprehensive assessment of predictive power, with support for neuroimaging features

Hyperparameter tuning for machine learning models using a distributed genetic algorithm

🦅Hyperparameter optimization for machine learning pipelines 🦅

Sklearndf ⭐ 59

DataFrame support for scikit-learn.

hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating the results on an independent validation set. hgboost can be applied for classification and regression tasks.

Datatap Python ⭐ 37

Focus on Algorithm Design, Not on Data Wrangling

Confounds ⭐ 35

Conquering confounds and covariates in machine learning

Offline Handwriting Recognition With Tensorflow ⭐ 30

Machine Learning Toolkits With Python ⭐ 26

Machine learning toolkits with Python

Machine_learning_a Z_all_codes_and_templates ⭐ 20

All codes, both created and optimized for best results from the SuperDataScience Course

Predicting Baseball Statistics ⭐ 14

Predicting Baseball Statistics: Classification and Regression Applications in Python Using scikit-learn

Pychemometrics ⭐ 13

pyChemometrics - Objects for multivariate analysis of chemometric and metabonomic datasets

Torch Handle ⭐ 13

TorchHandle makes your PyTorch development more efficient and make you use PyTorch more comfortable

An experiment control system for reproducible research

Tensorcross ⭐ 11

Cross Validation, Grid Search and Random Search for TensorFlow 2 Datasets

Confound_prediction ⭐ 10

Confound-isolating cross-validation approach to control for a confounding effect in a predictive model.

Keras Text Classification ⭐ 10

CNN text classification using keras

Applied Deep Learning With Keras ⭐ 9

Solve complex real-life problems with the simplicity of Keras

Assistant Cross Validation ⭐ 9

Python script to cross-validate an assistant workspace

Param Opt ⭐ 9

本项目开发了一个机器学习和深度学习的训练工具。该训练工具基于sklearn和pytorch，不仅支持

Target Likelihood Encoding ⭐ 8

Generate target statistics

DL tool for white matter hyperintensities segmentation

Capstoneproject_house_prices_prediction ⭐ 7

Understand the relationships between various features in relation with the sale price of a house using exploratory data analysis and statistical analysis. Applied ML algorithms such as Multiple Linear Regression, Ridge Regression and Lasso Regression in combination with cross validation. Performed parameter tuning, compared the test scores and suggested a best model to predict the final sale price of a house. Seaborn is used to plot graphs and scikit learn package is used for statistical analysi

Simple Linear Regression ⭐ 7

A python implementation of linear regression algorithm. (including Maximum Likelihood, Maximum a posterior, Bayesian)

Learn to use Support Vector Machines in Python(sklearn) and R

Spatial Kfold ⭐ 7

spatial resampling for more robust cross validation in spatial studies

Uri Url Classification Using Recurrent Neural Network Svm And Randomforest ⭐ 7

URI-URL Classification using Recurrent Neural Network, Support Vector and RandomForest. The Implementation results follows with classification report, confusion matrix and precision_recall_fscore_support for each validation result of a 10-fold crossval

Nested Cross Validation Comparison ⭐ 7

Experimenting with various implementations and methods of nested cross-validation in R and Python

Car Price Prediction Highly Comprehensive Linear Regression Project ⭐ 6

A Linear Regression model to predict the car prices for the U.S market to help a new entrant understand important pricing variables in the U.S automobile industry. A highly comprehensive analysis with detailed explanation of all steps; data cleaning, exploration, visualization, feature selection, model building, evaluation & MLR assumptions validity.

Timebasedcv ⭐ 6

Time based splits for cross validation

Wb_gdp_predict ⭐ 5

Predicting next year's GDP using ML (Python)

Keras Tuner Cv ⭐ 5

Extension for keras tuner that adds a set of classes to implement cross validation techniques.

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