I can not get this program to work.import numpy as npimport pandas as pd# Do not change these options; This allows the CodeGrade auto grading to function correctlypd.set_option('display.max_columns', None)import warningswarnings.filterwarnings('ignore')fileName = "JohnnyPiesData.csv"pie_df = pd.read_csv('JohnnyPiesData.csv')pie_dfpie_df =pie_df.drop(['Example'],axis=1);features = pie_df.drop(['Example'], axis = 1);response = pd.get_dummies(pie_df['Example'])pie_dffrom sklearn.linear_model import LinearRegressionfrom sklearn.metrics import accuracy_scorereg_model = LinearRegression()reg_model.fit(features, response)reg_model.coef_reg_model.intercept_preds = reg_model.predict (features)preds [preds <= 0.5] = 0preds[preds > 0.5] = 1resp_comp = response.copy()reg_outputs = [float(reg_model.predict(np.reshape(row, (1, -1)))) for row in features.itertuples(index=False)]predicted_resp = np.array([1 if reg_output > 0.5 else 0 for reg_output in reg_outputs])resp_comp = resp_comp.assign(Regression_Predictions = reg_outputs)resp_comp = resp_comp.assign(Predicted_Responses = predicted_resp)resp_compacc_score = accuracy_score(response, preds) D1202122232425262728File522930313233343536InsertX Cut[Copy ✓✔Format PainterClipboardNumberFontGAlignmentGUndo(i) POSSIBLE DATA LOSS Some features might be lost if you save this workbook in the comma-delimited (.csv) format. To preserve these features, save it in an Excel file format.AutoSave Off 8 JohnnyPiesData ✓4ReadyHHomePage Layout Formulas Data Review View✓ A^ A~A~PasteCircle ThickTriangle ThickCircle ThinABсDFG1 Example Crust Shap Crust Size Crust ShadFilling Size Filling Sha Class2 ex1Circle ThickThick Darkpos3 ex2Thick Darkpos4 ex3Thick Graypos5 ex4posGrayWhiteDarkWhite ThinDark ThinWhite ThinGray ThickWhite Thick6 ex5DarkWhiteDarkpos7 ex6pos8 ex7Whiteneg9 ex8Grayneg10 ex9DarknegGrayDarkThinThick11 ex10Whiteneg12 ex11White ThickDarkneg13 ex12White Thick Gray neg141516171819Square ThickCircle ThickCircle ThickSquare ThickTriangle ThinCircle ThickSquare ThickTriangle ThickJohnnyPies DataAccessibility: UnavailableCalibriType here to searchBICrust Shade+✓11H✓UEXO10Help=== = = B 五HCI,Cab Wrap TextMerge & CenterJKSearch (Alt+Q)LGeneral$%950000M>N5Conditional Format asFormatting TableONormalGoodPDon't show againStylesQBadRNeutralSave As...STTInsertUTDelete FormatCellsVWΣ. AutoSumFillClearXAYSort & Find &Filter SelectEditingGary NeislerYZ77°F Mostly cloudyGNmAnalyzeDataAnalysisAACommentsSensitivitySensitivityAB^4xAC9:00 AM9/9/2022Share100%

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Answered: I can not get this program to work.…

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Question

I can not get this program to work.

import numpy as np
import pandas as pd

# Do not change these options; This allows the CodeGrade auto grading to function correctly
pd.set_option('display.max_columns', None)
import warnings
warnings.filterwarnings('ignore')

fileName = "JohnnyPiesData.csv"
pie_df = pd.read_csv('JohnnyPiesData.csv')
pie_df

pie_df =pie_df.drop(['Example'],axis=1);
features = pie_df.drop(['Example'], axis = 1);
response = pd.get_dummies(pie_df['Example'])
pie_df

from sklearn.linear_model import LinearRegression
from sklearn.metrics import accuracy_score
reg_model = LinearRegression()
reg_model.fit(features, response)

reg_model.coef_
reg_model.intercept_

preds = reg_model.predict (features)
preds [preds <= 0.5] = 0
preds[preds > 0.5] = 1

resp_comp = response.copy()
reg_outputs = [float(reg_model.predict(np.reshape(row, (1, -1)))) for row in features.itertuples(index=False)]
predicted_resp = np.array([1 if reg_output > 0.5 else 0 for reg_output in reg_outputs])
resp_comp = resp_comp.assign(Regression_Predictions = reg_outputs)
resp_comp = resp_comp.assign(Predicted_Responses = predicted_resp)
resp_comp

acc_score = accuracy_score(response, preds)

D1
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File
5
2
29
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35
36
Insert
X Cut
[Copy ✓
✔Format Painter
Clipboard
Number
Font
G
Alignment
G
Undo
(i) POSSIBLE DATA LOSS Some features might be lost if you save this workbook in the comma-delimited (.csv) format. To preserve these features, save it in an Excel file format.
AutoSave Off 8 JohnnyPiesData ✓
4
Ready
H
Home
Page Layout Formulas Data Review View
✓ A^ A
~A~
Paste
Circle Thick
Triangle Thick
Circle Thin
A
B
с
D
F
G
1 Example Crust Shap Crust Size Crust ShadFilling Size Filling Sha Class
2 ex1
Circle Thick
Thick Dark
pos
3 ex2
Thick Dark
pos
4 ex3
Thick Gray
pos
5 ex4
pos
Gray
White
Dark
White Thin
Dark Thin
White Thin
Gray Thick
White Thick
6 ex5
Dark
White
Dark
pos
7 ex6
pos
8 ex7
White
neg
9 ex8
Gray
neg
10 ex9
Dark
neg
Gray
Dark
Thin
Thick
11 ex10
White
neg
12 ex11
White Thick
Dark
neg
13 ex12
White Thick Gray neg
14
15
16
17
18
19
Square Thick
Circle Thick
Circle Thick
Square Thick
Triangle Thin
Circle Thick
Square Thick
Triangle Thick
JohnnyPies Data
Accessibility: Unavailable
Calibri
Type here to search
B
I
Crust Shade
+
✓11
H✓
U
E
X
O
10
Help
==
= = = B 五
H
C
I
,C
ab Wrap Text
Merge & Center
J
K
Search (Alt+Q)
L
General
$%950000
M
>
N
5
Conditional Format as
Formatting Table
O
Normal
Good
P
Don't show again
Styles
Q
Bad
R
Neutral
Save As...
S
T
T
Insert
U
T
Delete Format
Cells
V
W
Σ. AutoSum
Fill
Clear
X
AY
Sort & Find &
Filter Select
Editing
Gary Neisler
Y
Z
77°F Mostly cloudy
GN
m
Analyze
Data
Analysis
AA
Comments
Sensitivity
Sensitivity
AB
^4x
AC
9:00 AM
9/9/2022
Share
100%

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