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covid_analysis
Commit 72d4fcce authored by Joaquin Torres's avatar Joaquin Torres
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parent 0aaace52
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Showing with 28 additions and 28 deletions
explainability/compute_shap_inter_vals.py
View file @ 72d4fcce
......@@ -16,10 +16,10 @@ from sklearn.tree import DecisionTreeClassifier
# --------------------------------------------------------------------------------------------------------
def read_test_data(attribute_names):
# Load test data
X_test_pre = np.load('../gen_train_data/data/output/pre/X_test_pre.npy', allow_pickle=True)
y_test_pre = np.load('../gen_train_data/data/output/pre/y_test_pre.npy', allow_pickle=True)
X_test_post = np.load('../gen_train_data/data/output/post/X_test_post.npy', allow_pickle=True)
y_test_post = np.load('../gen_train_data/data/output/post/y_test_post.npy', allow_pickle=True)
X_test_pre = np.load('../gen_train_data/output/pre/X_test_pre.npy', allow_pickle=True)
y_test_pre = np.load('../gen_train_data/output/pre/y_test_pre.npy', allow_pickle=True)
X_test_post = np.load('../gen_train_data/output/post/X_test_post.npy', allow_pickle=True)
y_test_post = np.load('../gen_train_data/output/post/y_test_post.npy', allow_pickle=True)
# Type conversion needed
data_dic = {
......@@ -36,7 +36,7 @@ if __name__ == "__main__":
# Setup
# --------------------------------------------------------------------------------------------------------
# Retrieve attribute names in order
attribute_names = list(np.load('../gen_train_data/data/output/attributes.npy', allow_pickle=True))
attribute_names = list(np.load('../gen_train_data/output/attributes.npy', allow_pickle=True))
# Reading data
data_dic = read_test_data(attribute_names)
method_names = {
......
explainability/compute_shap_vals.py
View file @ 72d4fcce
......@@ -16,10 +16,10 @@ from sklearn.tree import DecisionTreeClassifier
# --------------------------------------------------------------------------------------------------------
def read_test_data(attribute_names):
# Load test data
X_test_pre = np.load('../gen_train_data/data/output/pre/X_test_pre.npy', allow_pickle=True)
y_test_pre = np.load('../gen_train_data/data/output/pre/y_test_pre.npy', allow_pickle=True)
X_test_post = np.load('../gen_train_data/data/output/post/X_test_post.npy', allow_pickle=True)
y_test_post = np.load('../gen_train_data/data/output/post/y_test_post.npy', allow_pickle=True)
X_test_pre = np.load('../gen_train_data/output/pre/X_test_pre.npy', allow_pickle=True)
y_test_pre = np.load('../gen_train_data/output/pre/y_test_pre.npy', allow_pickle=True)
X_test_post = np.load('../gen_train_data/output/post/X_test_post.npy', allow_pickle=True)
y_test_post = np.load('../gen_train_data/output/post/y_test_post.npy', allow_pickle=True)
# Type conversion needed
data_dic = {
......@@ -36,7 +36,7 @@ if __name__ == "__main__":
# Setup
# --------------------------------------------------------------------------------------------------------
# Retrieve attribute names in order
attribute_names = list(np.load('../gen_train_data/data/output/attributes.npy', allow_pickle=True))
attribute_names = list(np.load('../gen_train_data/output/attributes.npy', allow_pickle=True))
# Reading data
data_dic = read_test_data(attribute_names)
method_names = {
......
explainability/fit_final_models.py
View file @ 72d4fcce
......@@ -18,22 +18,22 @@ from sklearn.tree import DecisionTreeClassifier
# --------------------------------------------------------------------------------------------------------
def read_training_data(attribute_names):
# Load ORIGINAL training data
X_train_pre = np.load('../gen_train_data/data/output/pre/X_train_pre.npy', allow_pickle=True)
y_train_pre = np.load('../gen_train_data/data/output/pre/y_train_pre.npy', allow_pickle=True)
X_train_post = np.load('../gen_train_data/data/output/post/X_train_post.npy', allow_pickle=True)
y_train_post = np.load('../gen_train_data/data/output/post/y_train_post.npy', allow_pickle=True)
X_train_pre = np.load('../gen_train_data/output/pre/X_train_pre.npy', allow_pickle=True)
y_train_pre = np.load('../gen_train_data/output/pre/y_train_pre.npy', allow_pickle=True)
X_train_post = np.load('../gen_train_data/output/post/X_train_post.npy', allow_pickle=True)
y_train_post = np.load('../gen_train_data/output/post/y_train_post.npy', allow_pickle=True)
# Load oversampled training data
X_train_over_pre = np.load('../gen_train_data/data/output/pre/X_train_over_pre.npy', allow_pickle=True)
y_train_over_pre = np.load('../gen_train_data/data/output/pre/y_train_over_pre.npy', allow_pickle=True)
X_train_over_post = np.load('../gen_train_data/data/output/post/X_train_over_post.npy', allow_pickle=True)
y_train_over_post = np.load('../gen_train_data/data/output/post/y_train_over_post.npy', allow_pickle=True)
X_train_over_pre = np.load('../gen_train_data/output/pre/X_train_over_pre.npy', allow_pickle=True)
y_train_over_pre = np.load('../gen_train_data/output/pre/y_train_over_pre.npy', allow_pickle=True)
X_train_over_post = np.load('../gen_train_data/output/post/X_train_over_post.npy', allow_pickle=True)
y_train_over_post = np.load('../gen_train_data/output/post/y_train_over_post.npy', allow_pickle=True)
# Load undersampled training data
X_train_under_pre = np.load('../gen_train_data/data/output/pre/X_train_under_pre.npy', allow_pickle=True)
y_train_under_pre = np.load('../gen_train_data/data/output/pre/y_train_under_pre.npy', allow_pickle=True)
X_train_under_post = np.load('../gen_train_data/data/output/post/X_train_under_post.npy', allow_pickle=True)
y_train_under_post = np.load('../gen_train_data/data/output/post/y_train_under_post.npy', allow_pickle=True)
X_train_under_pre = np.load('../gen_train_data/output/pre/X_train_under_pre.npy', allow_pickle=True)
y_train_under_pre = np.load('../gen_train_data/output/pre/y_train_under_pre.npy', allow_pickle=True)
X_train_under_post = np.load('../gen_train_data/output/post/X_train_under_post.npy', allow_pickle=True)
y_train_under_post = np.load('../gen_train_data/output/post/y_train_under_post.npy', allow_pickle=True)
# Type conversion needed
data_dic = {
......@@ -111,7 +111,7 @@ if __name__ == "__main__":
# Setup
# --------------------------------------------------------------------------------------------------------
# Retrieve attribute names in order
attribute_names = list(np.load('../gen_train_data/data/output/attributes.npy', allow_pickle=True))
attribute_names = list(np.load('../gen_train_data/output/attributes.npy', allow_pickle=True))
# Reading data
data_dic = read_training_data(attribute_names)
method_names = {
......
explainability/shap_plots.ipynb
View file @ 72d4fcce
......@@ -35,13 +35,13 @@
"outputs": [],
"source": [
"# Retrieve attribute names in order\n",
"attribute_names = list(np.load('../gen_train_data/data/output/attributes.npy', allow_pickle=True))\n",
"attribute_names = list(np.load('../gen_train_data/output/attributes.npy', allow_pickle=True))\n",
"\n",
"# Load test data\n",
"X_test_pre = np.load('../gen_train_data/data/output/pre/X_test_pre.npy', allow_pickle=True)\n",
"y_test_pre = np.load('../gen_train_data/data/output/pre/y_test_pre.npy', allow_pickle=True)\n",
"X_test_post = np.load('../gen_train_data/data/output/post/X_test_post.npy', allow_pickle=True)\n",
"y_test_post = np.load('../gen_train_data/data/output/post/y_test_post.npy', allow_pickle=True)\n",
"X_test_pre = np.load('../gen_train_data/output/pre/X_test_pre.npy', allow_pickle=True)\n",
"y_test_pre = np.load('../gen_train_data/output/pre/y_test_pre.npy', allow_pickle=True)\n",
"X_test_post = np.load('../gen_train_data/output/post/X_test_post.npy', allow_pickle=True)\n",
"y_test_post = np.load('../gen_train_data/output/post/y_test_post.npy', allow_pickle=True)\n",
"\n",
"# Type conversion needed \n",
"data_dic = {\n",
......
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