def run_dr_clustering(): deposit_data = load_cleanse_data() income_data = loadData() pcakMeans(deposit_data, 7, 'deposit', 'manhattan') # running PCA/kmeans for income Data pcakMeans(income_data, 4, 'income', 'euclidean') # running PCA/em for Deposit Data pcaem(deposit_data, 7, 'deposit', 'manhattan') # running PCA/em for Deposit Data pcaem(income_data, 4, 'income', 'euclidean') # ICA for deposit clustering icakMeans(deposit_data, 35, 'deposit', 'manhattan') icaem(deposit_data, 35, 'deposit', 'manhattan') # ICA for income clustering icakMeans(income_data, 12, 'income', 'euclidean') icaem(income_data, 12, 'income', 'euclidean') rpkMeans(deposit_data, 30, 'deposit', 'manhattan') rpem(deposit_data, 30, 'deposit', 'manhattan') # ICA for income clustering rpkMeans(income_data, 8, 'income', 'euclidean') rpem(income_data, 8, 'income', 'euclidean') uvfskMeans(deposit_data, 30, 'deposit', 'manhattan') uvfsem(deposit_data, 30, 'deposit', 'manhattan') uvfskMeans(income_data, 10, 'income', 'euclidean') uvfsem(income_data, 10, 'income', 'euclidean')
def performIncomePCA(): data = loadData() pca.perform_pca(data['features'], 'income') pca.validate_pca_nn(data, [4, 6, 8, 10, 12,14], 'income')
def performIncomeuvfs(): data = loadData() uvfs.validate_uvfs_nn(data, [4, 6, 8, 10, 12, 14],'income')
def performIncomeRandomProjection(): data = loadData() randomprojection.validate_rp_nn(data, [4, 6, 8, 10, 12, 14],'income')
def performIncomeICA(): data = loadData() ica.perform_ica(data['features'], 'income', [4, 6, 8, 10, 12, 14]) ica.validate_ica_nn(data, [4, 6, 8, 10, 12, 14], 'income')
def income_em(): data = loadData() print(data) estimate_em_k(data, 'income', 'plots/em/', 'euclidean') validate_em_k(data, 'plots/em/', 'income')
def income_clustering(): data = loadData() estimate_k(data, 'income', 'plots/kmeans/', 'euclidean') validate_k(data, 'plots/kmeans/', 'income')