even better version of 08

Zadanie_08_MLflow.py

@@ -14,13 +14,13 @@ import mlflow
 
 with mlflow.start_run():
 
-    batch_param = 16 #int(sys.argv[1]) if len(sys.argv) > 1 else 16
+    batch_param = int(sys.argv[1]) if len(sys.argv) > 1 else 16
-    epoch_param = 15 #int(sys.argv[2]) if len(sys.argv) > 2 else 15
+    epoch_param = int(sys.argv[2]) if len(sys.argv) > 2 else 15
 
     mlflow.log_param("batch_size", batch_param)
     mlflow.log_param("epochs", epoch_param)
 
-    wine=pd.read_csv('train.csv')
+    wine=pd.read_csv('winequality-red.csv')
 
     y = wine['quality']
     x = wine.drop('quality', axis=1)
@@ -44,6 +44,8 @@ with mlflow.start_run():
     scale = StandardScaler()
     scaled_x = scale.fit_transform(x)
 
+    x_train, x_test, y_train, y_test = train_test_split(scaled_x,yenc , test_size=0.2,train_size=0.8, random_state=21)
+
     NeuralModel = Sequential([
                             Dense(128, activation='relu', input_shape=(14,)),
                             Dense(32, activation='relu'),
@@ -57,13 +59,14 @@ with mlflow.start_run():
 
     NeuralModel.compile(optimizer=rms, loss='binary_crossentropy', metrics=['accuracy'])
 
-    NeuralModel.fit(scaled_x, yenc, batch_size= batch_param, epochs = epoch_param) #verbose = 1
+    NeuralModel.fit(x_train, y_train, batch_size= batch_param, epochs = epoch_param) #verbose = 1
 
-    #TO TYLKO NA POTRZEBY ZADANIA
+    y_pred = NeuralModel.predict(x_test)
-    y_pred = NeuralModel.predict(scaled_x)
 
     y_pred = np.around(y_pred, decimals=0)
 
-    results = accuracy_score(yenc,y_pred)
+    results = accuracy_score(y_test,y_pred)
+
+    print(f"accuracy: {results}")
 
     mlflow.log_metric("Accuracy", results)

mlruns/0/28466abc585446d78254527964ff8aaa/meta.yaml

@@ -0,0 +1,15 @@
+artifact_uri: file:///C:/Users/domstr2/Desktop/Git%20Repositories/ium_434788/mlruns/0/28466abc585446d78254527964ff8aaa/artifacts
+end_time: 1621171137099
+entry_point_name: ''
+experiment_id: '0'
+lifecycle_stage: active
+name: ''
+run_id: 28466abc585446d78254527964ff8aaa
+run_uuid: 28466abc585446d78254527964ff8aaa
+source_name: ''
+source_type: 4
+source_version: ''
+start_time: 1621171134077
+status: 3
+tags: []
+user_id: domstr2

mlruns/0/28466abc585446d78254527964ff8aaa/metrics/Accuracy

@@ -0,0 +1 @@
+1621171137096 1.0 0

mlruns/0/28466abc585446d78254527964ff8aaa/params/batch_size

@@ -0,0 +1 @@
+16

mlruns/0/28466abc585446d78254527964ff8aaa/params/epochs

@@ -0,0 +1 @@
+16

mlruns/0/28466abc585446d78254527964ff8aaa/tags/mlflow.source.git.commit

@@ -0,0 +1 @@
+b2447b18df29bc57f4a9ee2ac3f6d53a6f4f8ab8

mlruns/0/28466abc585446d78254527964ff8aaa/tags/mlflow.source.name

@@ -0,0 +1 @@
+Zadanie_08_MLflow.py

mlruns/0/28466abc585446d78254527964ff8aaa/tags/mlflow.source.type

@@ -0,0 +1 @@
+LOCAL

mlruns/0/28466abc585446d78254527964ff8aaa/tags/mlflow.user

@@ -0,0 +1 @@
+domstr2