This module does xxx. Objective? Use case?
Work flow Add a use case (for example, if I want h-cluster, how to set params)
Inputs
Outputs
Inputs :
| Id | label | Class | Description |
|---|---|---|---|
| analysis_data | Data files located in this project’s RAVE directory | ||
| check_scale | Z-score data | checkbox (logic) | if selected, z-scoring would be applied on the signals within the selected time window across electrodes |
| input_groups | Condition Group | list | The condition groups that we would like to study, with elements as selected conditions and given list element names as condition group name |
| input_method | Clustering Method | character | name of cluster algorithms (ex. ‘H-Clust’, ‘PAM’) |
| time_window | Time Window | number | a 2-element vector to indicate the time window range, the analysis would only apply on the power within the time window |
| distance_method | Clustering Distance Measurement | character | methods to calculate the distance (dissimilarity) for the clustering (ex. ‘euclidean’, ‘maximum’,“manhattan”, “canberra”, “minkowski”) |
| mds_distance_method | MDS Distance Measurement | methods to calculate the distance between points to generate the mds diagnosis (ex. ‘euclidean’, ‘maximum’,“manhattan”,“canberra”) | |
| op_run | Optimal Number of Clusters Analysis | checkbox | if selected, generate the plots of silhouette and SSE for different clustering methods to estimate the optimal number of clusters |
| do_run | Run Analysis | run the clustering analysis to generate all the plots and tables |
Outputs :
| Id | Label | Class | Description |
|---|---|---|---|
| cluster_plot | Cluster Visualization | graph | for each clusters, visualize the mean and point-wise standard deviation of the power against different conditions |
| mds_plot | MDS Diagnosis | graph | visualize the original high dimension data in two dimension space with MDS |
| cluster_membership_table | Clustering Membership | chart | tables shown which electrode from which subject is in which cluster |
| dendrogram_plot | Dendrogram | diagram | hierarchical clustering only; shows how the hierarchical arrangement happens among objects |
| optimal_cluster_number_plot | Optimal number of clusters | graph | visualize the silhouette and SSE for the different numbers of clustering, help determine the optimal numbers of clusters (a brief introduction of silhouette and SSE(elbow) method can be found here) |