How to Calculate Cosine Similarity in R
How to Calculate Cosine Similarity in R, The measure of similarity between two vectors in an inner product space is cosine similarity. The formula for two vectors, like A and B and the Cosine...
How to Calculate Cosine Similarity in R, The measure of similarity between two vectors in an inner product space is cosine similarity. The formula for two vectors, like A and B and the Cosine...
Pareto Chart in R, Pareto chart is a combination of a line graph and a bar chart used for visualization. A Pareto graph is a type of chart that displays the frequencies of the different categories with the cumulated frequencies of the categories. How to create...
How to Calculate MAPE in R, when want to measure the forecasting accuracy of a model the solution is MAPE. MAPE stands for mean absolute percentage error. The mathematical formula to calculate MAPE is:...
How to Calculate SMAPE in R?, SMAPE indicates the symmetric mean absolute percentage error.SMAPE is mainly used to measure the predictive accuracy of models. Mathematical formula is SMAPE = (1/n) * Σ(|forecast – actual|...
Mean Absolute Error in R, when we do modeling always need to measure the accuracy of the model fit. The mean absolute error (MAE) allows us to measure the accuracy of a given model....
Heteroscedasticity in Regression, one of the easiest ways to measure heteroscedasticity is while using the Breusch-Pagan Test. The test is mainly used to identify if heteroscedasticity is present in a regression analysis. This tutorial...
Boxplots in R, A boxplot is a plot that displays the five-digit summary of a dataset. The five-digit summary is the lowest value, the first quartile, the median, the third quartile, and the maximum value. We can use a boxplot to easily visualize a set of data. Principal component analysis (PCA)...
Calculate Phi Coefficient in R, first, we need to understand what is Phi Coefficient? It is a measurement of the degree of association between two binary variables. When it’s coming to inference it is similar to the...
Root Mean Square Error In R, The root mean square error (RMSE) allows us to measure how far predicted values are from observed values in a regression analysis. In other words, how concentrated the...
ANCOVA in R, Analysis of covariance is used to measure the main effect and interaction effects of categorical variables on a continuous dependent variable while controlling the effects of selected other continuous variables which...