Tag Archives: sklearn

Applied Data Science Coding with Python: SVM Algorithm

Applied Data Science Coding with Python: SVM Algorithm The Support Vector Machine (SVM) algorithm is a method for classification and regression in machine learning. It is used to find the best boundary (or hyperplane) that separates different classes in the dataset with the greatest possible margin. The SVM algorithm starts by mapping the input data …

Applied Data Science Coding with Python: Naive Bayes Algorithm

Applied Data Science Coding with Python: Naive Bayes Algorithm The Naive Bayes algorithm is a method for classification in machine learning. It is based on Bayes’ theorem which states that the probability of an event occurring is equal to the prior probability of the event multiplied by the likelihood of the event given certain evidence. …

Applied Data Science Coding with Python: LR Algorithm

Applied Data Science Coding with Python: LR Algorithm The Logistic Regression (LR) algorithm is a method for classification in machine learning. It is used to model the probability of a certain class or event occurring, given the values of certain features or inputs. The LR algorithm starts by finding the best set of coefficients that …

Applied Data Science Coding with Python: KNN Algorithm

Applied Data Science Coding with Python: KNN Algorithm The K-Nearest Neighbors (KNN) algorithm is a method for classification and regression in machine learning. It is based on the idea that similar data points tend to have similar outcomes or labels. The KNN algorithm works by finding the K number of data points in the training …

Applied Data Science Coding with Python: CART Algorithm

Applied Data Science Coding with Python: CART Algorithm The CART (Classification and Regression Tree) algorithm is a powerful tool for both classification and regression problems in machine learning. It is used to create a decision tree that can be used to make predictions based on the input data. The CART algorithm works by recursively splitting …

Applied Data Science Coding with Python: How to get Regression R_squared

How to get Regression R_squared R-squared is a statistical measure that helps us understand how well a regression model is able to explain the variation in the target variable. It is a value between 0 and 1, where a value closer to 1 indicates a better fit of the model to the data. To calculate …

Applied Data Science Coding with Python: How to get Regression MSE

How to get Regression MSE Regression is a statistical method that helps us understand the relationship between different variables. One way to evaluate the performance of a regression model is to calculate the Mean Squared Error (MSE). MSE is a measure of how well the model is able to predict the target variable. It is …

Applied Data Science Coding with Python: How to get Regression Metric MAE

How to get Regression Metric MAE Regression is a type of machine learning that is used to predict numerical values. One way to evaluate the performance of a regression model is to use a metric called Mean Absolute Error (MAE). To calculate MAE, you first need to have a dataset with both input variables (also …

Applied Data Science Coding with Python: How to get Classification Report

How to get Classification Report A classification report is a tool used in machine learning to evaluate the performance of a classification model. It is used to compare the predicted classes and the true classes of a dataset. The classification report in Python typically includes several metrics such as precision, recall, f1-score, and support. Precision …

Applied Data Science Coding with Python: How to get Classification LogLoss Metric

Applied Data Science Coding with Python: How to get Classification LogLoss Metric LogLoss, also known as logarithmic loss, is a performance metric commonly used in classification problems. It measures the difference between predicted probability and the true label. In simple terms, it calculates the error rate between the predicted values and the actual values. The …