def abalone(verbose=False, show_plots=False):
X_train, X_test, y_train, y_test = data_proc.process_abalone()
run_experiment('abalone',
X_train,
X_test,
y_train,
y_test,
verbose=verbose,
show_plots=show_plots)
def abalone(kernels, verbose=False, show_plots=False):
X_train, X_test, y_train, y_test = data_proc.process_abalone()
for col in X_train.columns:
X_train[col] = data_proc.scale_data(X_train[col])
X_test[col] = data_proc.scale_data(X_test[col])
for kernel in kernels:
run_experiment(kernel,
'abalone',
X_train,
X_test,
y_train,
y_test,
verbose=verbose,
show_plots=show_plots)
def abalone(verbose=False):
X, y = data_proc.process_abalone(scaler='minmax')
run_k_means('abalone', X, y, verbose=verbose)
run_expect_max('abalone', X, y, verbose=verbose)
def abalone_cluster(verbose=False, show_plots=False):
X, y = data_proc.process_abalone(scaler='minmax', tt_split=False)
# calculate baseline performance
base_X_train, base_X_test, base_y_train, base_y_test = data_proc.process_abalone(
tt_split=True)
run_experiment(
'abalone',
'baseline',
base_X_train,
base_X_test,
base_y_train,
base_y_test,
verbose=verbose,
show_plots=show_plots,
)
if verbose:
print("\nBaseline complete!\n", "------------------------------\n")
# calculate K-means performance
k_means_X_clusters = clustering.run_k_means('abalone',
X,
y,
dim_reduction=None,
verbose=verbose)
k_means_X_train, k_means_X_test, k_means_y_train, k_means_y_test = data_proc.process_abalone_w_clusters(
k_means_X_clusters, scaler='minmax')
run_experiment(
'abalone',
'kmeans',
k_means_X_train,
k_means_X_test,
k_means_y_train,
k_means_y_test,
verbose=verbose,
show_plots=show_plots,
)
if verbose:
print("\nK-means complete!\n", "------------------------------\n")
# calculate Expectation Maximization performance
em_X_clusters = clustering.run_expect_max('abalone',
X,
y,
dim_reduction=None,
verbose=verbose)
em_X_train, em_X_test, em_y_train, em_y_test = data_proc.process_abalone_w_clusters(
em_X_clusters, scaler='minmax')
run_experiment(
'abalone',
'em',
em_X_train,
em_X_test,
em_y_train,
em_y_test,
verbose=verbose,
show_plots=show_plots,
)
if verbose:
print("\nExpectation Maximization complete!\n",
"------------------------------\n")
def abalone_dr(verbose=False, show_plots=False):
X, y = data_proc.process_abalone(scaler='minmax', tt_split=False)
# calculate baseline performance
base_X_train, base_X_test, base_y_train, base_y_test = data_proc.process_abalone(
tt_split=True)
run_experiment(
'abalone',
'baseline',
base_X_train,
base_X_test,
base_y_train,
base_y_test,
verbose=verbose,
show_plots=show_plots,
)
if verbose:
print("\nBaseline complete!\n", "------------------------------\n")
# calculate PCA performance
pca_X = dim_reduction.run_pca('abalone', X, y, verbose=verbose)
pca_X_train, pca_X_test, pca_y_train, pca_y_test = train_test_split(
pca_X, y)
run_experiment(
'abalone',
'pca',
pca_X_train,
pca_X_test,
pca_y_train,
pca_y_test,
verbose=verbose,
show_plots=show_plots,
)
if verbose: print("\nPCA complete!\n", "------------------------------\n")
# calculate ICA performance
ica_X = dim_reduction.run_ica('abalone', X, y, verbose=verbose)
ica_X_train, ica_X_test, ica_y_train, ica_y_test = train_test_split(
ica_X, y)
run_experiment(
'abalone',
'ica',
ica_X_train,
ica_X_test,
ica_y_train,
ica_y_test,
verbose=verbose,
show_plots=show_plots,
)
if verbose: print("\nICA complete!\n", "------------------------------\n")
# calculate RP performance
rp_X = dim_reduction.run_rp('abalone', X, y, verbose=verbose)
rp_X_train, rp_X_test, rp_y_train, rp_y_test = train_test_split(rp_X, y)
run_experiment(
'abalone',
'rp',
rp_X_train,
rp_X_test,
rp_y_train,
rp_y_test,
verbose=verbose,
show_plots=show_plots,
)
if verbose: print("\nRP complete!\n", "------------------------------\n")
# calculate DT_FI performance
dt_fi_X = dim_reduction.run_dt_fi('abalone', X, y, verbose=verbose)
dt_fi_X_train, dt_fi_X_test, dt_fi_y_train, dt_fi_y_test = train_test_split(
dt_fi_X, y)
run_experiment(
'abalone',
'dt_fi',
dt_fi_X_train,
dt_fi_X_test,
dt_fi_y_train,
dt_fi_y_test,
verbose=verbose,
show_plots=show_plots,
)
if verbose:
print("\nDT_FI complete!\n", "------------------------------\n")
def abalone(verbose=False):
X, y = data_proc.process_abalone(scaler='minmax', tt_split=False)
run_pca('abalone', X, y, verbose=verbose)
run_ica('abalone', X, y, verbose=verbose)
run_rp('abalone', X, y, verbose=verbose)
run_dt_fi('abalone', X, y, verbose=verbose)