troubleshooting Question

Python - exporting results to .csv file

Avatar of csehz
csehzFlag for Hungary asked on
11 Comments1 Solution5064 ViewsLast Modified:
Dear Experts,

I have the following Python code which predicts result on the iris dataset in the frame of machine learning.

# -*- coding: utf-8 -*-

# Load libraries
import pandas
from import scatter_matrix
import matplotlib.pyplot as plt
from sklearn import model_selection
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix
from sklearn.metrics import accuracy_score
from sklearn.linear_model import LogisticRegression
from sklearn.tree import DecisionTreeClassifier
from sklearn.neighbors import KNeighborsClassifier
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.naive_bayes import GaussianNB
from sklearn.svm import SVC

# Load dataset
path = "C:\\Users\\zc\\Downloads\\Daily files\\Machine Learning\\IrisGenerated.csv"
names = ['sepal-length', 'sepal-width', 'petal-length', 'petal-width', 'class']
dataset = pandas.read_csv(path, names=names)

# Split-out validation dataset
array = dataset.values
X = array[:,0:4]
Y = array[:,4]
validation_size = 0.20
seed = 7
X_train, X_validation, Y_train, Y_validation = model_selection.train_test_split(X, Y, test_size=validation_size, random_state=seed)

# Test options and evaluation metric
seed = 7
scoring = 'accuracy'

# Fit the model
model = KNeighborsClassifier(), Y_validation)

# save the model to disk
filename = 'finalized_model.sav'
joblib.dump(model, filename)

# load the model from disk
loaded_model = joblib.load(filename)
result = loaded_model.score(X_validation, Y_validation)

detailed_result = model.predict(X)


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Basically the results are in the 'detailed_result' variable at the end, could you please advise with the syntax how that could be exported as .csv file from Python?

Thanks in advance,

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