Package index • klassets

Simulation of Quasi-Anscombe data sets

Functions to simulate data sets with related regression patterns.

sim_quasianscombe_set_1(): Generate quasi Anscombe data sets Type 1
sim_quasianscombe_set_2(): Generate quasi Anscombe data sets Type 2: No linear relationship
sim_quasianscombe_set_3(): Generate quasi Anscombe data sets Type 3: Extreme values (a.k.a Outliers)
sim_quasianscombe_set_4(): Generate quasi Anscombe data sets Type 4: 2 Clusters
sim_quasianscombe_set_5(): Generate quasi Anscombe data sets Type 5: Heteroskedasticity
sim_quasianscombe_set_6(): Generate quasi Anscombe data sets Type 6: Simpson's Paradox

Functions to simulate data and explain clustering algorithms.

sim_groups(): Generate data sets to apply clustering algorithms
fit_kmeans(): Fit K-means to klassets_cluster object
fit_hclust(): Fit Hierarchical Clustering to klassets_cluster object using stats::hclust
fit_statskmeans(): Fit K-means to klassets_cluster object using stats::kmeans
kmeans_iterations(): Generate intermediate iterations when performing K-means

Functions to simulate data and explain classification algorithms.

sim_response_xy(): Generate data sets to apply binary classifiers
fit_logistic_regression(): Fit Logistic regression to klassets_response_xy object
fit_classification_tree(): Fit classification tree to klassets_response_xy object
fit_classification_random_forest(): Fit classification random forest to klassets_response_xy object
fit_knn(): Fit K Nearest Neighbours to klassets_response_xy object

Functions to simulate data and explain regression algorithms.

sim_xy(): Generate data sets to apply regression methods
fit_linear_model(): Fit Linear model to klassets_xy object
fit_regression_tree(): Fit regression tree to klassets_xy object
fit_linear_model_tree(): Fit Linear Model tree to klassets_xy object
fit_regression_random_forest(): Fit regression random forest to klassets_xy object
fit_loess(): Fit Local polynomial regression to klassets_xy object
fit_mars(): Fit Multivariate Adaptive Regression Splines to klassets_xy object

Functions and data sets to fit models to MNIST data and compare predictive performance and variable importance.

Small data sets used in examples and teaching material.