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Jack-Cherish / Machine-Learning

⚡机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归

python machine-learning svm regression logistic python3 adaboost smo knn decision-tree navie-bayes-algorithm adaboost-algorithm

Updated Jul 7, 2021
Python

Mayurji / MLWithPytorch

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Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

machine-learning linear-regression machine-learning-algorithms python3 pytorch naive-bayes-classifier pca-analysis gaussian-mixture-models logistic-regression decision-trees ridge-regression naive-bayes-algorithm kmeans-clustering svm-classifier lasso-regression knn-classification pytorch-implementation tfidf-vectorizer adaboost-algorithm

Updated Dec 15, 2021
Python

lesleyping / Machine-Learning

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Image classification using SVM, KNN, Bayes, Adaboost, Random Forest and CNN.Extracting features and reducting feature dimension using T-SNE, PCA, LDA.

machine-learning random-forest pca image-classification t-sne lda bayes-classifier svm-classifier fourier-features knn-classification cnn-classification sift-features adaboost-algorithm

Updated Aug 12, 2020
Python

matheastevens / Ecommerce-Sales-Analysis

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Customer Lifetime Value, Returns Predictions, Recommender system and sales analysis on UC Irvine online sales dataset.

machine-learning-algorithms recommender-system customer-lifetime-value adaboost-algorithm

Updated Mar 23, 2021
Jupyter Notebook

obynio / adaboost

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A parallelised facial recognition program written from scratch in C with minimal dependencies

adaboost haar-cascade facial-detection haar-classifiers adaboost-algorithm

Updated Jul 25, 2021
C

Automobile dataset for used Car Price Analysis to predict the price of a vehicle with their features and performance factor to provide the exact value of a vehicle for buyer seller satisfaction using exploratory data analysis and machine learning models.

python linear-regression exploratory-data-analysis machine-learning-algorithms ridge-regression grid-search lasso-regression automobile random-forest-regression adaboost-algorithm lightgbm-regressor

Updated Jun 6, 2020
Jupyter Notebook

tkhan11 / Dtreehub

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Dtreehub is a lightweight decision tree framework for Python with categorical feature support. It covers regular decision tree algorithms: ID3, C4.5, CART, CHAID and regression tree, random forest and adaboost.

classifier random-forest id3 cart decision-trees chaid regression-trees adaboost-algorithm

Updated Jul 10, 2021
Python

stanleyowomero / Employee-Absenteeism

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Employee-Absenteeism-Project-Work

random-forest logistic-regression standardization adaboost guassian knn-classifier svc-svm adaboost-algorithm

Updated Jun 26, 2020
Jupyter Notebook

FawazQutami / AdaBoost_Classification_sklearn

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AdaBoost classification using sklearn

python machine-learning validation scikit-learn sklearn machine-learning-algorithms data-transformation cross-validation adaboost adaboost-algorithm label-encoder adaboostclassifier

Updated Mar 27, 2021
Python

RickFSA / Lending_Club_Default_Prediction

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Classify default borrowers from initial loan application for Lending Club

xgboost-algorithm random-forest-classifier unbalanced-data adaboost-algorithm qlattice

Updated Mar 2, 2021
Jupyter Notebook

FawazQutami / AdaBoost_Regression_sklearn

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AdaBoost Regression using sklearn

python machine-learning scikit-learn sklearn machine-learning-algorithms cross-validation feature-selection adaboost feature-engineering adaboosting adaboost-learning adaboost-algorithm model-selection-boosting adaboos-regression

Updated Mar 31, 2021
Python

PeterSchuld / Disaster-Response-Pipeline-

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Project No.2 (Data Engineering) in the Data Scientist Nanodegree program. Build a machine learning pipeline to categorize emergency messages based on the need communicated by the sender.

sqlite-database flask-application nltk-library random-forest-classifier etl-pipeline sklearn-pipeline adaboost-algorithm

Updated May 1, 2021
Jupyter Notebook

sumankumarsubudhi / Diabetes-Case-Study

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Machine Learning Model helps to gain an understanding of how to optimize a number of models using grid searching

machine-learning supervised-learning grid-search adaboost-algorithm

Updated Jul 19, 2019
HTML

kpratikin / Credit-Card-Fraud

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Identify fraudulent credit card transactions so that customers are not charged for items that they did not purchase. (Python, Logistic Regression Classifier, Unbalanced dataset).

boost cross-validation xgboost normalization smote fraud-detection oversampling undersampling ensemble-machine-learning unbalanced-data adaboost-algorithm

Updated Oct 14, 2019
Jupyter Notebook

FawazQutami / AdaBoost

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AdaBoost: math under the hood

python machine-learning machine-learning-algorithms regression classification adaboost adaboost-algorithm adaboost-model

Updated Mar 27, 2021
Python

philsaurabh / XGBoost-and-Adaboost-Example

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A simple example project on XGBoost and Adaboost.

python machine-learning ipython-notebook xgboost-algorithm adaboost-algorithm

Updated Aug 30, 2020
Jupyter Notebook

diana-corona / adaboost-bag-words-sentiment-analysis

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adaboost-bag-words-sentiment-analysis

bag-of-words adaboost sentiment-classification adaboost-algorithm adaboostclassifier

Updated Sep 13, 2021
Python

jeevankande / Ensemble-Techniques

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Ensemble methods is a machine learning technique that combines several base models in order to produce one optimal predictive model. To better understand this definition lets take a step back into ultimate goal of machine learning and model building. This is going to make more sense as I dive into specific examples and why Ensemble methods are used.

random-forest cross-validation gradient-boosting voting-classifier xgboost-algorithm adaboost-algorithm stacking-ensemble bagging-ensemble