我正在尝试使用scikit将我的csv文件包含多少个1和0返回到我的结果，但是当我运行该程序时，没有任何人可以看到代码的问题，据我所知它应该可以正常工作但什么也没发生 这是我运行程序时得到的结果： # -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import classification_report
def load_data_from_csv (input_csv):
df = pd.read_csv(input_csv, header=0)
csv_headings = list(df.columns.values)
feature_names = csv_headings[:len(csv_headings) - 1 ]
label_name = csv_headings[len(csv_headings) - 1:len(csv_headings)][0]
df = df._get_numeric_data()
numpy_array = df.as_matrix()
number_of_rows, number_of_columns = numpy_array.shape
instances = numpy_array[:, 0:number_of_columns - 1]
labels = []
for label in numpy_array[:, number_of_columns - 1:number_of_columns].tolist():
labels.append(label[0])
return feature_names, instances, labels
input_training_csv='Downloads\csv\csv/reviews_Video_Games_training.csv'
input_test_csv='Downloads\csv\csv/reviews_Video_Games_test.csv'
training_feature_names, training_instances, training_labels = load_data_from_csv(input_csv=input_training_csv)
test_feature_names, test_instances, test_labels = load_data_from_csv(input_csv=input_test_csv)
classifier = KNeighborsClassifier(n_neighbors=2)
classifier.fit(training_instances, training_labels)
predicted_test_labels = classifier.predict (test_instances)
print(classification_report(test_labels, predicted_test_labels, digits=3))
runfile('D:/bradl/spyder/PROJECTS/csv run.py', wdir='D:/bradl/spyder/PROJECTS')
0 个答案:
没有答案