GitHub topics: grid-search-cross-validation
mnochtioui/House-Prices---Advanced-Regression-Techniques
Detailed walkthrough of a data science project for the Kaggle House Prices challenge, covering data cleaning, EDA, feature engineering, and regression modeling.
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farshad257/Regrassion_Income_Forcasting
A powerful stacked ensemble model for income prediction, combining GradientBoosting, AdaBoost, Bagging, Linear Regression, and Decision Trees. Achieves an impressive R² of 0.8761 on the RoS_sample_submission dataset.
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farshad257/NLP_IMDB
A simple Bernoulli Naive Bayes model achieved 94% accuracy on the IMDB sentiment analysis task. Despite its simplicity, it performed exceptionally well.
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connect-web/OSRS-ML
MlFlow Project creating pipelines and using Grid-Search Cross Validation to find optimal parameters for Old School Runescape Machine Learning datasets.
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felicity12345/Marketing-Data-Analysis-Project
Marketing Data Analysis Project
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vaitybharati/SVM
SVM
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deepakdeedar/Machine-Learning-Reboot
This repo contains all machine learning algorithms using python and scikit-learn
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gauravsharma884/Big-Data-And-Data-Analytics
This repository contains all the work projects carried out with respect to learning and experiments on Big Data Analytics. The scripts are formed to build machine learning models for future predictions.
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avestura/scikit-heart-disease-classifier
💚 A heart disease classifier using 4 SVM kernels and decision trees, with PCA, ROC, pruning, grid search cv, confusion matrix, and more
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iamkirankumaryadav/Loan
Loan Approval Prediction
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iamkirankumaryadav/Improvement
Improving a Machine Learning Model
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iamkirankumaryadav/Churn
Customer Churn Prediction
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iamkirankumaryadav/Applied-Machine-Learning
Applied Machine Learning ( End to End ) Classification Models
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bhulston/Random-Forest-on-Cancer-Classification
Built Random Forest classifier from scratch on top of Scikit Learn decision trees. Using Scikit Learn to create data cleaning pipelines, perform grid searches for hyper parameter tuning, and decision tree modeling
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santiagoahl/world-happiness
A Machine Learning Model built in scikit-learn using Support Vector Regressors, Ensemble modeling with Gradient Boost Regressor and Grid Search Cross Validation.
Language: Python - Size: 7.8 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 4 - Forks: 0
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 candidates more likely to have the visa certified.
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uzunb/house-prices-prediction-LGBM
This repo has been developed for the Istanbul Data Science Bootcamp, organized in cooperation with İBB and Kodluyoruz. Prediction for house prices was developed using the Kaggle House Prices - Advanced Regression Techniques competition dataset.
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angeloruggieridj/MLPClassifier-with-GridSearchCV-Iris
Experimental using on Iris dataset of MultiLayerPerceptron (MLP) tested with GridSearch on parameter space and Cross Validation for testing results.
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natvalenz/uglyXmas
Retail data analysis using machine learning techniques in Python and Sklearn packages to help Ugly Christmas Party determine how many sweaters to order for each ugly Christmas sweater design created.
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AmishaMurarka/Facebook-Comment-Volume-Prediction
Data in the social networking services is increasing day by day. So, there is heavy requirement to study the highly dynamic behavior of the users towards these services. The task here is to estimate the comment count that a post is expected to receive in next few(H) hours. Data has been scraped from one of the most popular social networking sites - Facebook.
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SurayaSumona/Telecom_Customer_Churn_Prediction
Machine Learning with Python
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TonmoyTalukder/Churning-Telecom-Company-Prediction
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DanielMSousa/Regression-evaluator
This project is made for search the best regression model based in some metrics training some models and evaluating them
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somjit101/DS-Logistic-Regression
A simple implementation of the Logistic Regression Classifier on the Breast Cancer Dataset with L1 regularization and GridSearch for hyperparameter tuning.
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