random-forest-classification

There are 0 repository under random-forest-classification topic.

jstrzempko / GEE-Random-Forest-HBM-Tutorial
Habitat Suitability Modeling with Random Forest Classification in Google Earth Engine
google-earth-engine random-forest-classification habitat-suitability tutorial
Language:JavaScript 12
Joycechidi / MachineLearning
All my Machine Learning Projects from A to Z in (Python & R)
datapreprocessing python r regression simple-linear-regression multiple-linear-regression support-vector-regression--svr polynomial-regression decision-tree-regression random-forest-regression evaluating-regression-models-perf regularization-methods classification logistic-regression k-nearest-neighbors-k-nn support-vector-machine-svm kernel-svm naive-bayes decision-tree-classification random-forest-classification
Language:Jupyter Notebook 4
kumar-rishav3101 / Health-Predictor
Predict your diseases based on the symptoms provided And Image Processing technique is used to predict the skin cancer
machine-learning decision-tree-classifier random-forest random-forest-classification disease-prediction disease-classification disease-dataset symptoms symptoms-analysis symptoms-dataset django website cnn convolutional-neural-networks deep-learning skin-cancer skin-cancer-detection skin-cancer-data
Language:Python 4
ThomasJNicoletti / Pulsar
A Data Mining Streamlit Application for Astrophysical Prediction using Random Forest Classification in Python
data-mining streamlit astrophysics prediction random-forest-classification python mahalanobis-distance pulsar integrated-profile dm-snr-curve statistics model
Language:Python 4
gagejane / Suicide-bombings
Used the Global Terrorism Database to Explore Features of Suicide Bombings
lda roc-curve roc-auc decision-trees random-forest-classification gradient-boosting machine-learning feature-importance geospatial-data global-terrorism-database suicide-bombings terrorism gensim
Language:Jupyter Notebook 3
dshah98 / Machine_Learning_with_Python
Full machine learning practical with Python.
linear-regression multiple-linear-regression polynomial-regression support-vector-regression decision-tree-regression random-forest-regression logistic-regression knn-classification support-vector-machine kernel-svm naive-bayes-classification decision-tree-classification random-forest-classification k-means-clustering hierarchical-clustering apriori-algorithm eclat-algorithm natural-language-processing artificial-neural-networks convolutional-neural-network
Language:Jupyter Notebook 2
dshah98 / Machine_Learning_with_R
Full machine learning practical with R.
linear-regression multiple-linear-regression polynomial-regression support-vector-regression decision-tree-regression random-forest-regression logistic-regression knn-classification support-vector-machine kernel-svm naive-bayes-classification decision-tree-classification random-forest-classification k-means-clustering hierarchical-clustering apriori-algorithm eclat-algorithm natural-language-processing artificial-neural-networks convolutional-neural-network
Language:R 2
nitingour1203 / credit-card-default-prediction
If you miss payments or you don't pay the right amount, your creditor may send you a default notice, also known as a notice of default. If the default is applied it'll be recorded in your credit file and can affect your credit rating. An account defaults when you break the terms of the credit agreement.
decision-tree-classification gaussian-naive-bayes k-nearest-neighbour random-forest-classification stochastic-gradient-descent support-vector-machine grid-search-on-logistic-regression-model
Language:Jupyter Notebook 2
ThomasJNicoletti / Driver
Driver Analysis with Factors and Forests: An Automated Data Science Tool using Python
python data-mining statistics model prediction driver-analysis factor-analysis random-forest-classification data-science business social-science mahalanobis-distance importance-analysis
Language:Python 2
Akanksha-15-Priya / Marketing-Campaign-For-Banking-Product-ML
k-nearest-neighbors decision-tree-classification random-forest-classification
Language:Jupyter Notebook 1
Ansu-John / ML-Classification
Build and evaluate classification model using PySpark 3.0.1 library.
classification classification-algorithms pyspark-mllib decision-tree-classifier spark decision-tree-classification random-forest-classification gbt-classification binaryclassificationevaluator multiclassclassificationevaluator logistic-regression regression-methods multilayer-perceptron linear-support-vector-machine one-vs-rest naive-bayes-classifier factorization-machines
Language:Jupyter Notebook 1
girirajv10 / Random-Forest-Classification
Random forests is a supervised learning algorithm. It can be used both for classification and regression. It is also the most flexible and easy to use algorithm. A forest is comprised of trees. It is said that the more trees it has, the more robust a forest is. Random forests creates decision trees on randomly selected data samples, gets prediction from each tree and selects the best solution by means of voting. It also provides a pretty good indicator of the feature importance.
random-forest random-forest-classifier random-forest-classification machine-learning classification-algorithm ml scikit-learn supervised-learning tensorflow
Language:Jupyter Notebook 1
PialGhosh2233 / Liver_Cirrhosis_Prediction_using_Machine_Learning
knn knn-algorithm knn-classification knn-classifier machine-learning machine-learning-algorithms random-forest random-forest-algorithm random-forest-classification random-forest-classifier artificial-intelligence artificial-intelligence-projects machine-learning-projects data-science data-science-projects ml-project python python-project
Language:Jupyter Notebook 1
Sabaudian / Music_Genre_Classification_project
Audio Pattern Recognition project - Music Genre Classification
artificial-intelligence audio-analysis audio-classification audio-processing genre-classification genres-classification k-nearest-neighbours k-nn machine-learning music-genre-classification music-information-retrieval neural-network preprocessing preprocessing-data python random-forest random-forest-classification svm svm-classifier
Language:Python 1
amit-raj-repo / ML-Random-Forest-Python
This repository will help in understanding the basic concept of Random Forest algorithm and will also learn how to optimize the hyperparameters and prevent overfitting.
random-forest random-forest-classifier bootstrap bagging-trees random-forest-classification
Language:Jupyter Notebook 0
bhavya840 / ML-Classification
In this project the data is been used from UCI Machinery Repository. Main aim of this project is to predict telling tumor of each patient is Benign (class – 2) or Malignant (class – 4) the models used are – Decision tree Classification, Logistic Regression, K-Nearest Neighbors, SVM, Kernel SVM, Naïve-Bayes and Random Forest Classification.
machine-learning-algorithms svm kernel-svm logistic-regression decision-tree-classification random-forest-classification naive-bayes-classifier knearest-neighbors
Language:Jupyter Notebook 0
debasishray16 / StockPredictor
"Stock Predictor" project basically aims to provide a visual representation and analysis of data related to time-series data which is constantly changing. This provides a dashboard to user displaying current trends and stocks data which uses ML like "LSTM" and "Random Forest" model.
artificial-intelligence css javascript linear-regression-python machine-learning html5 lstm-neural-networks random-forest yfinance-data-warehouse random-forest-classification tailwind-css keras-neural-networks reactjs streamlit tensorflow-models
Language:Python 0
GOWTHAMJEEVANANTHAM / Disease-Prediction-Case-Study
Predicted the disease using the symptoms observed in the patients.
knn-classification decision-tree-classifier random-forest-classification gradient-boosting logistic-regression
Language:Jupyter Notebook 0
HanifaElahi / Machine-Learning
MACHINE LEARNING ALGORITHMS
machine-learning linear-regression multiple-linear-regression polynomial-regression support-vector-regression decision-tree-regression random-forest-regression logistic-regression k-nearest-neighbors naive-bayes-classification support-vector-machine decision-tree-classification random-forest-classification k-means-clustering dbscan-clustering hierarchical-clustering hierarchial-clustering facial-recognition
Language:Jupyter Notebook 0
kunjan-mhaske / Risky-loan-prediction-using-ML-in-R-Studio
Implemented and compared Random Forest, Decision Tree, KNN, SVM, and Logistic Regression outcomes with a confusion matrix. Concluded that Random Forest achieved the highest accuracy of 85% to predict the loan status for investors.
random-forest-classification rstudio knn-classification svm-classifier logistic-regression linear-regression python3
Language:HTML 0
red-wine-quality
pronzzz / red-wine-quality
Machine Learning model to predict Red Wine Quality using Random Forest Classifier
gridsearchcv hyperparameter-tuning random-forest random-forest-classification random-forest-classifier
Language:Jupyter Notebook 0
rubelbd82 / Machine-Learning
Machine learning algorithms implemented in python. Some are implemented in R. Algorithms include XGBoost, Convolutional Neural Network, Recursive Neural Network, Support Vector Machine, K-nearest neighbors, Naive Bayes, Natural Language Processing
machine learning convolutional-neural-networks xgboost random-forest-classification naive-bayes scikitlearn-machine-learning recurrent-neural-networks
Language:Python 0
amiegirl / Fellowship_AI
Sentiment Analysis of Movies Dataset
matplotlib scikit-learn wordcloud decision-tree-classification logisticregression pandas random-forest-classification
Language:Jupyter Notebook
arqchicago / rfc-heart
random forest classification (with hyperparameter tuning) on heart disease dataset.
random-forest-classification hyperparameter-tuning model-evaluation-metrics
Language:Python
gonultasbu / random-forest-stump
Minimal implementation of Random Forest classifier using decision stumps and bootstrap sampling without sklearn.
random-forest random-forest-classification random-forest-classifier randomforest
Language:Python
handesarica / digital-addiction-analysis
Data analysis project on Digital Addiction for master thesis
classification digital-addiction machine-learning machine-learning-algorithms random-forest-algorithm random-forest-classification clustering clustering-algorithm k-means-clustering decision-tree knn logistic-regression naive-bayes random-forest svm
Language:Jupyter Notebook
lezippo / PredictStudentsDropoutAndAcademicSuccess
Prediction of students' dropout using classification models. Data visualisation, feature selection, dimensionality reduction, model selection and interpretation, parameters tuning.
classification cross-validation data-visualization decision-tree-classification dimensionality-reduction exploratory-data-analysis exploratory-data-visualizations feature-importance feature-selection grid-search knn-classification model-evaluation model-interpretation pca random-forest-classification tsne tuning-parameters xgboost-classification
Language:Jupyter Notebook

random-forest-classification

jstrzempko / GEE-Random-Forest-HBM-Tutorial

Joycechidi / MachineLearning

kumar-rishav3101 / Health-Predictor

ThomasJNicoletti / Pulsar

gagejane / Suicide-bombings

dshah98 / Machine_Learning_with_Python

dshah98 / Machine_Learning_with_R

nitingour1203 / credit-card-default-prediction

ThomasJNicoletti / Driver

Akanksha-15-Priya / Marketing-Campaign-For-Banking-Product-ML

Ansu-John / ML-Classification

girirajv10 / Random-Forest-Classification

PialGhosh2233 / Liver_Cirrhosis_Prediction_using_Machine_Learning

Sabaudian / Music_Genre_Classification_project

amit-raj-repo / ML-Random-Forest-Python

bhavya840 / ML-Classification

debasishray16 / StockPredictor

GOWTHAMJEEVANANTHAM / Disease-Prediction-Case-Study

HanifaElahi / Machine-Learning

kunjan-mhaske / Risky-loan-prediction-using-ML-in-R-Studio

pronzzz / red-wine-quality

rubelbd82 / Machine-Learning

amiegirl / Fellowship_AI

arqchicago / rfc-heart

gonultasbu / random-forest-stump

handesarica / digital-addiction-analysis

lezippo / PredictStudentsDropoutAndAcademicSuccess