jprdonnelly/MachineLearningNotebooks
1
0
Fork 0
mirror of https://github.com/Azure/MachineLearningNotebooks.git synced 2025-12-21 18:15:13 -05:00
Code Issues Projects Releases Wiki Activity

Delete train.py

Browse Source
This commit is contained in:
Shané Winner
2019-08-21 10:31:26 -07:00
committed by GitHub
parent 9eaab2189d
commit fd4de05ddd
1 changed files with 0 additions and 37 deletions
Download Patch File Download Diff File Expand all files Collapse all files

37
work-with-data/datasets/datasets-tutorial/train-dataset/train.py
View File

@@ -1,37 +0,0 @@
import azureml.dataprep as dprep
import azureml.core
import pandas as pd
import logging
import os
import datetime
import shutil
from azureml.core import Workspace, Datastore, Dataset, Experiment, Run
from sklearn.model_selection import train_test_split
from azureml.core.compute import ComputeTarget, AmlCompute
from azureml.core.compute_target import ComputeTargetException
from sklearn.tree import DecisionTreeClassifier
run = Run.get_context()
workspace = run.experiment.workspace
dataset_name = 'clean_Titanic_tutorial'
dataset = Dataset.get(workspace=workspace, name=dataset_name)
df = dataset.to_pandas_dataframe()
x_col = ['Pclass', 'Sex', 'SibSp', 'Parch']
y_col = ['Survived']
x_df = df.loc[:, x_col]
y_df = df.loc[:, y_col]
x_train, x_test, y_train, y_test = train_test_split(x_df, y_df, test_size=0.2, random_state=223)
data = {"train": {"X": x_train, "y": y_train},
"test": {"X": x_test, "y": y_test}}
clf = DecisionTreeClassifier().fit(data["train"]["X"], data["train"]["y"])
print('Accuracy of Decision Tree classifier on training set: {:.2f}'.format(clf.score(x_train, y_train)))
print('Accuracy of Decision Tree classifier on test set: {:.2f}'.format(clf.score(x_test, y_test)))