![]() ![]() Bootstrap Aggregation – A bagging technique that fits decision trees on bootstrap samples of the training data.Gradient Tree Boosting – One of the powerful boosting algorithms works on the principle of reducing the bias in predictions.ADAboost – An ensemble machine learning algorithm that converts the weak learners to strong learners for better performance.XGBoost – Extreme Gradient Boosting or XGBoost algorithm works on an ensemble approach that combines the predictions of weak models to produce a strong prediction.r2, adjusted r2, mean squared error, etc.Confusion matrix – To evaluate the true positive/negative, false positive/negative outcomes in the model.Classification reports – To evaluate the model on various metrics like recall, precision, f-support, etc.Principal Component Analysis – PCA follows the same approach in handling the multidimensional data. ![]() Linear Discriminant Analysis – LDA or linear discriminant analysis to reduce or optimize the dimensions in the multidimensional data.Dimensionality reduction – Handling multi dimensional data and standardizing the features for easier computation.K-means – The k-means algorithm that can be used for clustering problems in an unsupervised learning approach.Time Series Forecasting – Making use of time series data, gathering insights and useful forecasting solutions using time series forecasting. ![]()
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