Add MLPClassifier to models

This commit is contained in:
coolneng 2020-11-10 21:54:22 +01:00
parent 7568aedf94
commit 525d231838
Signed by: coolneng
GPG Key ID: 9893DA236405AF57
1 changed files with 4 additions and 1 deletions

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@ -2,6 +2,7 @@ from numpy import mean
from sklearn.metrics import confusion_matrix, accuracy_score, roc_auc_score
from sklearn.model_selection import cross_val_score
from sklearn.naive_bayes import GaussianNB
from sklearn.neural_network import MLPClassifier
from sklearn.neighbors import KNeighborsClassifier
from sklearn.preprocessing import scale
from sklearn.svm import LinearSVC
@ -19,6 +20,8 @@ def choose_model(model):
return KNeighborsClassifier(n_neighbors=10)
elif model == "tree":
return DecisionTreeClassifier(random_state=42)
elif model == "neuralnet":
return MLPClassifier(hidden_layer_sizes=10)
def predict_data(data, target, model):
@ -53,7 +56,7 @@ def evaluate_performance(confusion_matrix, accuracy, cv_score, auc):
def main():
data, target = parse_data(source="data/mamografia.csv", action="drop")
predict_data(data=data, target=target, model="gnb")
predict_data(data=data, target=target, model="neuralnet")
if __name__ == "__main__":