You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Amend the current dataset with other strong motion data - but first understand and describe the attributes in each file
Apply SVM to see if the margins can be increased between the clusters
Also see if MLP can classify the data to find other classes of interest.
Try Naive Bayesian multi classify because the data is parametric or LabelEncoding will parametrize the categorical data
K-means is ideal because it's unsupervised statistical learning but can we come up with a meaningful set of classes that describes the behavior of the SM DB data?
same with Random Forests to allow for using N-samples of features and datasets. It requires labeled data for supervised learning
The text was updated successfully, but these errors were encountered:
K-means is ideal because it's unsupervised statistical learning but can we come up with a meaningful set of classes that describes the behavior of the SM DB data?
same with Random Forests to allow for using N-samples of features and datasets. It requires labeled data for supervised learning
The text was updated successfully, but these errors were encountered: