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Collect import statements

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Along the way, switch to importing modules instead of classes
This commit is contained in:
Brett Cannon
2017-06-05 14:51:42 -07:00
parent 003979dd8c
commit b1c26888f1
1 changed files with 10 additions and 9 deletions
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samples/features/machine-learning-services/python/getting-started/rental-prediction/rental_prediction.sql
+10 -9
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@@ -27,23 +27,24 @@ BEGIN
@language = N'Python'
, @script = N'
from sklearn import linear_model
import pickle
df = rental_train_data
# Get all the columns from the dataframe.
columns = df.columns.tolist()
# Store the variable well be predicting on.
target = "RentalCount"
from sklearn.linear_model import LinearRegression
# Initialize the model class.
lin_model = LinearRegression()
lin_model = linear_model.LinearRegression()
# Fit the model to the training data.
lin_model.fit(df[columns], df[target])
import pickle
#Before saving the model to the DB table, we need to convert it to a binary object
trained_model = pickle.dumps(lin_model)
'
@@ -75,7 +76,7 @@ AS
BEGIN
DECLARE @py_model varbinary(max) = (select model from rental_py_models where model_name = @model);
EXEC sp_execute_external_script
EXEC sp_execute_external_script
@language = N'Python'
, @script = N'
@@ -83,7 +84,7 @@ BEGIN
import pickle
rental_model = pickle.loads(py_model)
df = rental_score_data
#print(df)
@@ -106,7 +107,7 @@ lin_mse = mean_squared_error(linpredictions, df[target])
#print(lin_mse)
import pandas as pd
predictions_df = pd.DataFrame(lin_predictions)
predictions_df = pd.DataFrame(lin_predictions)
OutputDataSet = pd.concat([predictions_df, df["RentalCount"], df["Month"], df["Day"], df["WeekDay"], df["Snow"], df["Holiday"], df["Year"]], axis=1)
'
, @input_data_1 = N'Select "RentalCount", "Year" ,"Month", "Day", "WeekDay", "Snow", "Holiday" from rental_data where Year = 2015'
@@ -114,7 +115,7 @@ OutputDataSet = pd.concat([predictions_df, df["RentalCount"], df["Month"], df["D
, @params = N'@py_model varbinary(max)'
, @py_model = @py_model
with result sets (("RentalCount_Predicted" float, "RentalCount" float, "Month" float,"Day" float,"WeekDay" float,"Snow" float,"Holiday" float, "Year" float));
END;
GO