Commit feaaafd4 authored by Valerio Maggio's avatar Valerio Maggio
Browse files

updated code with renamed load_nb_seqc function

parent 6be97062
......@@ -9,7 +9,7 @@ import pandas as pd
from collections import OrderedDict
from dap.deep_learning_dap import DeepLearningDAP
from dataset import load_nb_target, load_nb_camda
from dataset import load_nb_target, load_nb_seqc
from dataset import EFS_LAB, OS_LAB
from sklearn.metrics import roc_auc_score
......@@ -642,7 +642,7 @@ if __name__ == '__main__':
if args.dataset == 'TARGET':
load_ds_fn = load_nb_target
else:
load_ds_fn = load_nb_camda
load_ds_fn = load_nb_seqc
# Load Dataset
# ============
......
......@@ -5,7 +5,7 @@ CDRP-A Deep AutoEncoder for NB Dataset
import os
from dap.deep_learning_dap import DeepLearningDAPRegr
from dap.dap import DAPRegr
from dataset import load_nb_target, HR_LAB, load_nb_camda
from dataset import load_nb_target, HR_LAB, load_nb_seqc
from keras.backend import floatx
from keras.engine import Input, Model
......@@ -265,7 +265,7 @@ def main():
if args.dataset == 'TARGET':
load_ds_fn = load_nb_target
else:
load_ds_fn = load_nb_camda
load_ds_fn = load_nb_seqc
# Load Dataset
# ============
......
......@@ -10,7 +10,7 @@ import argparse
from collections import OrderedDict
from dap.deep_learning_dap import DeepLearningDAP
from dataset import load_nb_target, EFS_LAB, OS_LAB, load_nb_camda
from dataset import load_nb_target, EFS_LAB, OS_LAB, load_nb_seqc
from sklearn.metrics import roc_auc_score
from dap.metrics import (KCCC_discrete, accuracy, sensitivity, specificity,
......@@ -516,7 +516,7 @@ if __name__ == '__main__':
if args.dataset == 'TARGET':
load_ds_fn = load_nb_target
else:
load_ds_fn = load_nb_camda
load_ds_fn = load_nb_seqc
# Load Dataset
# ============
......
......@@ -4,7 +4,7 @@ Multi-Layer Perceptron DAP Runner on NB Dataset
import os
from dap.deep_learning_dap import DeepLearningDAP
from dataset import load_nb_target, load_nb_camda
from dataset import load_nb_target, load_nb_seqc
from dataset import EFS_LAB, OS_LAB, HR_LAB
import argparse
......@@ -139,7 +139,7 @@ def main():
if args.dataset == 'TARGET':
load_ds_fn = load_nb_target
else:
load_ds_fn = load_nb_camda
load_ds_fn = load_nb_seqc
# Load Dataset
# ============
......
......@@ -4,7 +4,7 @@ Random Forest DAP Runner on NB Dataset
import os
from dap.runners import RandomForestRunnerDAP
from dataset import load_nb_target, load_nb_camda
from dataset import load_nb_target, load_nb_seqc
from dataset import EFS_LAB, OS_LAB, HR_LAB
import argparse
......@@ -83,7 +83,7 @@ def main():
if args.dataset == 'TARGET':
load_ds_fn = load_nb_target
else:
load_ds_fn = load_nb_camda
load_ds_fn = load_nb_seqc
# Load Dataset
# ============
......
......@@ -4,7 +4,7 @@ SVM DAP Runner for NB Dataset
import os
from dap.runners import SupportVectorRunnerDAP
from dataset import load_nb_target, load_nb_camda
from dataset import load_nb_target, load_nb_seqc
from dataset import EFS_LAB, OS_LAB, HR_LAB
import argparse
......@@ -82,7 +82,7 @@ def main():
if args.dataset == 'TARGET':
load_ds_fn = load_nb_target
else:
load_ds_fn = load_nb_camda
load_ds_fn = load_nb_seqc
# Load Dataset
# ============
......
......@@ -7,7 +7,7 @@ Dataset
import os
from dap.runners import RandomForestRunnerDAP
from dataset import load_nb_camda, OS_LAB
from dataset import load_nb_seqc, OS_LAB
class RandomForestDeepFeaturesDAP(RandomForestRunnerDAP):
......@@ -67,9 +67,9 @@ def main():
test_data_fpath = os.path.join(os.path.abspath(os.path.dirname(__file__)),
'data', '..', 'OS32_SEQC', 'SEQC2_OS_32_test.csv')
dataset = load_nb_camda(dataset_name='SEQC2_OS32_HRONLY',
training_data_fpath=training_data_fpath,
test_data_fpath=test_data_fpath, hr_only=True)
dataset = load_nb_seqc(dataset_name='SEQC2_OS32_HRONLY',
training_data_fpath=training_data_fpath,
test_data_fpath=test_data_fpath, hr_only=True)
print('RUNNING ON DATASET {}'.format(dataset.dataset_name.upper()))
# ============
......
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