Awesome Open Source
Search
Programming Languages
Languages
All Categories
Categories
About
Search results for regression models classification model
classification-model
x
regression-models
x
6 search results found
Dominance Analysis
⭐
128
This package can be used for dominance analysis or Shapley Value Regression for finding relative importance of predictors on given dataset. This library can be used for key driver analysis or marginal resource allocation models.
Machineshop
⭐
62
MachineShop: R package of models and tools for machine learning
Website
⭐
53
Website sources for Applied Machine Learning for Tabular Data
Ml Hub
⭐
33
A Hub for all your Machine Learning Projects ranging from Beginner to Intermediate level. Get started with your Open Source and Machine Learning Journey with this beginner-friendly repository.
Btc_data
⭐
23
This repository contains the code and datasets for creating the machine learning models in the research paper titled "Time-series forecasting of Bitcoin prices using high-dimensional features: a machine learning approach"
Tf 1d 2d Resnetv1 2 Seresnet Resnext Seresnext
⭐
18
Models supported: ResNet, ResNetV2, SE-ResNet, ResNeXt, SE-ResNeXt [layers: 18, 34, 50, 101, 152] (1D and 2D versions with DEMO for Classification and Regression).
Deep Learning Workshop
⭐
14
The repository contains python codes, which I have developed as the facilitator of the two consecutive Deep Learning Workshops (I and II) for the master's students of computer science, University of Windsor.
Bess
⭐
12
Best Subset Selection algorithm for Regression, Classification, Count, Survival analysis
Forest Fire Prediction
⭐
10
Project for Predicting Algerian Forest Fires and Fire Weather Index Using Machine Learning with Python.
Data_science_introduction_with_python
⭐
8
En este proyecto de GitHhub podrás encontrar parte del material que utilizo para impartir las clases de Introducción a la Ciencia de Datos (Data Science) con Python.
1-6 of 6 search results
Privacy
|
About
|
Terms
|
Follow Us On Twitter
Copyright 2018-2024 Awesome Open Source. All rights reserved.