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xgboost-classifier

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ShivamVadalia / Underwater-Waste-Detection-Using-YoloV8-And-Water-Quality-Assessment

Neural Ocean is a project that addresses the issue of growing underwater waste in oceans and seas. It offers three solutions: YoloV8 Algorithm-based underwater waste detection, a rule-based classifier for aquatic life habitat assessment, and a Machine Learning model for water classification as fit for drinking or irrigation or not fit.

python machine-learning deep-learning pytorch statistical-analysis object-detection denoising-images dark-channel-prior xgboost-classifier rule-based-classifier yolov8

Updated Jun 12, 2023
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ashishrana1501 / Forest-Fire-Prediction

Algerian Forest Fire Prediction

python flask data-science machine-learning deployment modeling linear-regression sklearn jupyter-notebook feature-selection logistic-regression feature-engineering hyperparameter-tuning random-forest-classifier random-forest-regression xgboost-regression xgboost-classifier randomizedsearchcv

Updated Jul 3, 2024
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czaloumi / fire-risk-analysis

Machine Learning in Python to assess fire risk in satellite imagery and environmental conditions.

neural-network risk-analysis satellite-imagery cnn-model fire-detection smoke-detection xgboost-classifier forest-fires fire-images fire-risk

Updated May 4, 2021
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amzn / confident-sinkhorn-allocation

Pseudo-labeling for tabular data

tabular-data semi-supervised-learning pseudo-labeling xgboost-classifier sinkhorn-algorithm uncertainty-estimations

Updated Jun 18, 2024
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DandiMahendris / Auto-Insurance-Fraud-Detection

This research goal is to build binary classifier model which are able to separate fraud transactions from non-fraud transactions.

machine-learning gradient-boosting-classifier fraud-detection xgboost-classifier

Updated Nov 14, 2023
HTML

Abdullah2020 / Hamoye-2022-Capstone-Project_Neural_Network_Group

This is the repository of Hamoye 2022 Summer Internship Capstone Project by Neural-Network Team

exploratory-data-analysis dnn evaluation-metrics knn-classification random-forest-classifier classification-models xgboost-classifier

Updated Nov 13, 2022
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apoorvaKR12695 / Mobile-Price-Range-Prediction

Supervised ML- Built a Multi-Class classification model to find the relation between features of a mobile phone(RAM, Internal Memory etc) and its selling price. Model will predict the price range indicating how high the price is.

hyperparameter-optimization confusion-matrix multi-class-classification random-forest-classifier xgboost-classifier

Updated Jul 7, 2022
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edaaydinea / OP1-Prediction-of-the-Different-Progressive-Levels-of-Alzheimer-s-Disease

This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD).

data-science machine-learning deep-neural-networks tensorflow neural-networks logistic-regression keras-neural-networks chi-square-test random-forest-classifier alzheimer-disease-prediction xgboost-classifier anova-test lightgbm-classifier catboost-classifier multi-layer-perceptron-classifier

Updated Nov 6, 2022
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adelelwan24 / Prediction-of-Obesity-Risk

This project tackles the growing concern of obesity by developing a model to predict an individual's risk. By analyzing various factors, we aim to identify people who might be more susceptible to weight gain and related health problems.

python scikit-learn eda xgboost-classifier lgbmclassifier

Updated Apr 26, 2024
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mandar196 / Hate_Speech_Detection-NLP

Created Hate speech detection model using Count Vectorizer & XGBoost Classifier with an Accuracy upto 0.9471, which can be used to predict tweets which are hate or non-hate.

python nlp text-classification hatespeech countvectorizer porter-stemmer xgboost-classifier

Updated Oct 11, 2020
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gauravmalakar08 / Coronavirus-Tweet-Sentiment-Analysis

Analysing Of Tweet Sentiments Using Supervised Learning Classification Algorithms

python nlp machine-learning eda logistic-regression decision-tree-classifier svm-classifier lemmatization tweet-analysis stemming-algorithm tweet-sentiment-analysis xgboost-classifier coronavirus

Updated Sep 26, 2024
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AliAmini93 / Fault-Detection-in-DC-microgrids

Using DIgSILENT, a smart-grid case study was designed for data collection, followed by feature extraction using FFT and DWT. Post-extraction, feature selection. CNN-based and extensive machine learning techniques were then applied for fault detection.

neural-network random-forest svm cnn feature-selection fft dwt data-augmentation mutual-information linear-discriminant-analysis pearson-correlation grid-search-hyperparameters xgboost-classifier anova-analysis digsilent

Updated Aug 25, 2024
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slrvv / CENTRE

machine-learning computational-biology r-package enhancer-prediction xgboost-classifier enhancer-gene

Updated Apr 23, 2024
R

Davidelvis / BankClientTermDeposit_Prediction

Bank Institution Term Deposit Predictive Model

machine-learning random-forest exploratory-data-analysis pca logistic-regression multilayer-perceptron-network imbalanced-learning robust-scaling onehot-encoding xgboost-classifier

Updated Aug 29, 2020
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rochitasundar / Customer-profiling-using-ML-EasyVisa

The aim is to find an optimal ML model (Decision Tree, Random Forest, Bagging or Boosting Classifiers with Hyper-parameter Tuning) to predict visa statuses for work visa applicants to US. This will help decrease the time spent processing applications (currently increasing at a rate of >9% annually) while formulating suitable profile of candidate…

decision-tree-classifier gradient-boosting-classifier f1-score random-forest-classifier grid-search-hyperparameters precision-recall accuracy-metrics xgboost-classifier stacking-ensemble adaboostclassifier bagging-ensemble grid-search-cross-validation

Updated Jan 20, 2022
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Pradnya1208 / Detecting-Parkinsons-Disease

The objective of this projects is to build a model to accurately detect the presence of Parkinson’s disease in an individual.

machine-learning healthcare classification-model parkinsons-detection xgboost-classifier

Updated Jan 23, 2022
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karthik-d / SnakeCLEF-2022-using-Network-Ensembles

Scripts, figures and working notes for the participation in SnakeCLEF-2022, part of the 13th CLEF Conference, 2022

machine-learning deep-learning tensorflow keras xgboost gradient-boosting-classifier imageclef boosting-tree lifeclef clef xgboost-classifier boosting-ensemble

Updated Mar 3, 2023
Python

Tanzanian-Waterpoint-Analysis-and-Classifictation

merb92 / Tanzanian-Waterpoint-Analysis-and-Classifictation

Predict the operational status of waterpoints to help the Tanzanian Government provide more clean water to its population using a Machine Learning Classifier

imbalanced-data smote multiclass-classification random-forest-classifier xgboost-classifier water-infrastructure

Updated Feb 11, 2021
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vinamrata-git / Chess-winner-prediction

Predict the winning probability of white player in a chess game on the basis of first move of white player and first move of black player. In the dataset all the set of moves are given but I choose to predict the white winner the first move

scikit-learn logistic-regression decision-tree-classifier svm-classifier random-forest-classifier knn-classifier catboost-model xgboost-classifier adaboostclassifier auc-score white-player

Updated Sep 6, 2022
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ppokhare / Handling-Imbalanced-Dataset-for-classification-task

Using various ML models and Neural Networks with Focal Loss function to predict fraudulent credit card transactions.

neural-networks imbalanced-data classification-task focal-loss xgboost-classifier

Updated Oct 16, 2021
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