444 Open source projects that are alternatives of or similar to Breast-Cancer-Scikitlearn

Machine learning algorithm such as KNN,Naive Bayes,Logistic Regression,SVM,Decision Trees,Random Forest,k means and Truncated SVD on amazon fine food review

Python code for common Machine Learning Algorithms

Formed trajectories of sets of points.Experimented on finding similarities between trajectories based on DTW (Dynamic Time Warping) and LCSS (Longest Common SubSequence) algorithms.Modeled trajectories as strings based on a Grid representation.Benchmarked KNN, Random Forest, Logistic Regression classification algorithms to classify efficiently t…

文本分类基准测试

经典机器学习算法的极简实现

Text Classification Algorithms: A Survey

Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

🏭 JavaScript Machine Learning Toolkit

텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)

🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!

In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.

This repo contains regression and classification projects. Examples: development of predictive models for comments on social media websites; building classifiers to predict outcomes in sports competitions; churn analysis; prediction of clicks on online ads; analysis of the opioids crisis and an analysis of retail store expansion strategies using…

🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.

机器学习教程，本教程包含基于numpy、sklearn与tensorflow机器学习，也会包含利用spark、flink加快模型训练等用法。本着能够较全的引导读者入门机器学习。

A document covering machine learning basics. 🤖📊

📈 Click-Through Rate Prediction using Logistic Regression and Tree Algorithms

Simple machine learning library / 簡單易用的機器學習套件

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

A curated list of data mining papers about fraud detection.

I will update this repository to learn Machine learning with python with statistics content and materials

Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.

This is the implementation of Sparse Projection Oblique Randomer Forest

Machine Learning with the NSL-KDD dataset for Network Intrusion Detection

Simple Implementation of Network Intrusion Detection System. KddCup'99 Data set is used for this project. kdd_cup_10_percent is used for training test. correct set is used for test. PCA is used for dimension reduction. SVM and KNN supervised algorithms are the classification algorithms of project. Accuracy : %83.5 For SVM , %80 For KNN

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.

Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting (GBDT, GBRT, GBM), Random Forest and Adaboost w/categorical features support for Python

Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning

Machine Learning library for the web and Node.

ML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python

several methods for text classification

Forecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning to Forecast Stock Return. Approach Used by Hedge Funds to Select Tradeable Stocks

Heart Disease prediction using 5 algorithms

Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)

利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

In this work, we propose a deterministic version of Local Interpretable Model Agnostic Explanations (LIME) and the experimental results on three different medical datasets shows the superiority for Deterministic Local Interpretable Model-Agnostic Explanations (DLIME).

Go Scoring API for PMML

Matlab library for gradient descent algorithms: Version 1.0.1

Final project of IBM's course https://www.coursera.org/learn/machine-learning-with-python on coursera

🍊 📊 💡 Orange: Interactive data analysis

Machine learning for C# .Net

Machine Learning models from scratch with a better visualisation

A SVM model that classifies the reviews as real or fake. Used both the review text and the additional features contained in the data set to build a model that predicted with over 85% accuracy without using any deep learning techniques.

An Interactive Approach to Understanding Supervised Learning Algorithms

Machine Learning University: Decision Trees and Ensemble Methods

FUKinect-Fall dataset was created using Kinect V1. The dataset includes walking, bending, sitting, squatting, lying and falling actions performed by 21 subjects between 19-72 years of age.

A tool for visualizing the structure and performance of Random Forests 🌳

Misc Statistics and Machine Learning codes in R

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

中文文本分类实践，基于搜狗新闻语料库，采用传统机器学习方法以及预训练模型等方法

(BOW, TF-IDF, Word2Vec, BERT) Word Embeddings + (SVM, Naive Bayes, Decision Tree, Random Forest) Base Classifiers + Pre-trained BERT on Tensorflow Hub + 1-D CNN and Bi-Directional LSTM on IMDB Movie Reviews Dataset

Top 5th percentile solution to the Kaggle knowledge problem - Bike Sharing Demand

Master's degree project: Development of a trading algorithm which uses supervised machine learning classification techniques to generate buy/sell signals

Predicting the winner of 2019 cricket world cup using random forest algorithm

Repository for the AdaptiveRandomForest algorithm implemented in MOA 2016-04

Machine Learning Lectures at the European Space Agency (ESA) in 2018

This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.

Information Retrieval in High Dimensional Data (class deliverables)

Interactive Visual Machine Learning Demos.