# Plot cumulative validated explained variance for each variable in Y hop.explainedVariance(model, individual=True) # In[9]: # Plot cumulative validated explained variance in X. hop.explainedVariance(model, which=['X']) # In[10]: hop.scores(model) # In[11]: hop.correlationLoadings(model) # In[12]: # Plot X loadings in line plot hop.loadings(model, weights=False, line=True) # In[13]: # Plot regression coefficients hop.coefficients(model, comp=[3]) # --- # ### Accessing numerical results
# Plot cumulative validated explained variance in X. hop.explainedVariance(model, which='X') # In[10]: hop.scores(model) # In[11]: hop.correlationLoadings(model) # In[12]: # Plot X loadings in line plot hop.loadings(model, weights=True, line=True) # In[13]: # Plot regression coefficients hop.coefficients(model, comp=3)