`K_corrplot()` is a wrapper around `corrplor::corrplot()` that returns a coorplot for visualizing the similarity matrix of site and background bags.
K_corrplot(K, train_data, clusters = 4)
| [K] | - Similarity Kernel Matrix |
|---|---|
| [list] | - training data |
| [scalar] | - clusters |
- a correlation matrix object
This function is a wrapper of `corrplot::corrplot()` with defaults and hierarchical clustering order. The inputs are the similarity kernel matirx `K`, the `train_data` used to creat `K`, and the number of clusters to display. The `train_data` is only used to procure the labels for site and background bags.
# NOT RUN { ##### Logistic Mean Embedding KRR Model #### Build Kernel Matrix K <- build_K(train_data, sigma = sigma, dist_metric = dist_metric, progress = FALSE) #### Train KLR model train_log_pred <- KLR(K, train_presence, lambda, 100, 0.001, verbose = 2) ### Plot K Matrix K_corrplot(K,train_data,clusters=4) # }