Improving a Machine Learning Model
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Updated
Jun 5, 2020 - Jupyter Notebook
Improving a Machine Learning Model
Experimental using on Iris dataset of MultiLayerPerceptron (MLP) tested with GridSearch on parameter space and Cross Validation for testing results.
Applied SVC classifier and Logistic Regression classifier algorithm onto credit card transaction dataset to detect any fraud.
SVM
💚 A heart disease classifier using 4 SVM kernels and decision trees, with PCA, ROC, pruning, grid search cv, confusion matrix, and more
Customer Churn Prediction
Loan Approval Prediction
A simple implementation of the Logistic Regression Classifier on the Breast Cancer Dataset with L1 regularization and GridSearch for hyperparameter tuning.
This project is made for search the best regression model based in some metrics training some models and evaluating them
Text Mining Competition
Machine Learning with Python
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…
This repo contains all machine learning algorithms using python and scikit-learn
I leveraged an algorithmic approach for document classification and document clustering. Various models have been trained for document classification and they all have been evaluated using performance metrics followed by tuning of the model hyper-parameters to reach the most accurate classification. Additionally, a model has been trained for doc…
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.
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 site…
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.
GridSearchCV For Model optimization
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