Health-insurance-cross-sell-prediction
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Updated
Mar 26, 2024 - Jupyter Notebook
Health-insurance-cross-sell-prediction
Develop supervised model which predict the loan defaulter in python using XGBClassifer
Clustering bank loan customers using KMeans clustering and predicting their loan statuses using XGBClassifier. The prediction model is explained with SHAP values.
Malware Detection is a Kaggle Competition held privately which detects the probability of a machine being infected with malware or not given various features of each machine.
Segmenting customers of an audiobook platform and predicting their future purchase.
Weather Prediction With Gradient Boost
ReneWind operates wind farms. Unexpected turbine failures are presenting operational and financial problems. This project uses machine learning to develop a model that accurately predict component failure, which will give the firm more control over maintenance scheduling, costs and power generation.
Метод опорних векторів -Support Vector Machine, SVM. Дерева рішень - RandomForestClassifier, XGBClassifier
In this project, I have created a Machine Learning model using XGBClassifier to Detect Parkinsons Disease with eXtreme Gradient Boosting (XGBoost).
This is the first project to be completed in Upskill ISA Intelligent Machines. The project was done after the end of the competition. The XGBClassifier used in this model obtained 0.950844 public scores on Kaggle.
Different classification algorithms to predict the species of Iris flowers
In this problem i have tried to explain how XGB algorithm works in case of classification. I have also stated the accuracy score at the end for our XGBClassifier model. The confusion matrix has also been shown for the same. I have used the Kaggle Dataset - Titanic Survivors csv file.
Detecting Parkinson Using extreme gradient boosting(XGBOOSTING) Algorithm.
Задача от Яндекс.Практикум и Samokat.tech – реализовать векторный поиск и решить усечённую задачу матчинга
classifying a patient has a heart disease or not
MlFlow Project creating pipelines and using Grid-Search Cross Validation to find optimal parameters for Old School Runescape Machine Learning datasets.
Develop a supervised model which predict whether or not participate in financial market in Python and using multivariate analysis ,determine key factors that lead to participation in financial market
In this Python machine learning project, using the Python libraries scikit-learn, numpy, pandas, and xgboost, I have build a model using an XGBClassifier. We’ll load the data, get the features and labels, scale the features, then split the dataset, build an XGBClassifier, and then calculate the accuracy of our model.
Detecting Parkinson's using the XGBClassifier
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