Question

# -*- coding: utf-8 -*-
"""
Created on Wed Apr 26 21:28:31 2017

@author: Chirantan
"""

import pandas
from pandas.tools.plotting 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
url = "https://archive.ics.uci.edu/ml/machine-learning-databases/yeast/yeast.data"
names = ['Sequence Name','mcg', 'gvh', 'alm', 'mit', 'erl','pox','vac','nuc']
dataset = pandas.read_csv(url, names=names, delim_whitespace=True)


# shape
print(dataset.shape)

# head
print(dataset.head(20))

# descriptions
print(dataset.describe())
# class distribution
#print(dataset.groupby('').size())
# box and whisker plots
dataset.plot(kind='box', subplots=True, layout=(10,10), sharex=False, sharey=False)
plt.show()
# histograms
dataset.hist()
plt.show()
# scatter plot matrix
scatter_matrix(dataset)
plt.show()
# histograms
dataset.hist()
plt.show()
# scatter plot matrix
scatter_matrix(dataset)
plt.show()
# Split-out validation dataset
array = dataset.values
X = array[:,0:9]
Y = array[:,9]#HERE IS THE ERROR
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'
# Spot Check Algorithms
models = []
models.append(('LR', LogisticRegression()))
models.append(('LDA', LinearDiscriminantAnalysis()))
models.append(('KNN', KNeighborsClassifier()))
models.append(('CART', DecisionTreeClassifier()))
models.append(('NB', GaussianNB()))
models.append(('SVM', SVC()))
# evaluate each model in turn
results = []
names = []
for name, model in models:
    kfold = model_selection.KFold(n_splits=10, random_state=seed)
    cv_results = model_selection.cross_val_score(model, X_train, Y_train, cv=kfold, scoring=scoring)
    results.append(cv_results)
    names.append(name)
    msg = "%s: %f (%f)" % (name, cv_results.mean(), cv_results.std())
    print(msg)

# Compare Algorithms
fig = plt.figure()
fig.suptitle('Algorithm Comparison')
ax = fig.add_subplot(111)
plt.boxplot(results)
ax.set_xticklabels(names)
plt.show()

# Make predictions on validation dataset
#knn = KNeighborsClassifier()
svm = SVC()
svm.fit(X_train, Y_train)
predictions = svm.predict(X_validation)
#knn.fit(X_train, Y_train)
#predictions = knn.predict(X_validation)
print(accuracy_score(Y_validation, predictions))
print(confusion_matrix(Y_validation, predictions))
print(classification_report(Y_validation, predictions))

我正在尝试使用不同的分类器来处理来自UCI存储库的多类酵母数据集。使用Iris数据集的上述代码一切正常，只有以下更改

# Split-out validation dataset
array = dataset.values
X = array[:,0:4]
Y = array[:,4]
validation_size = 0.20

但是，当我这样做时，它无法使用Yeast数据集

# Split-out validation dataset
array = dataset.values
X = array[:,0:9]
Y = array[:,9]
validation_size = 0.20

这是错误消息

  File "<ipython-input-40-707d4eef8576>", line 55, in <module>
    Y = array[:,9]

IndexError: index 9 is out of bounds for axis 1 with size 9

我不明白这个.array存储数据集的值，现在数组[：，9]会给我最后一列。我错了吗？请帮助。

Answer 1

array没有索引为9的列。它有9列，最后一列有索引8.（因为第一列的索引为0。）

我在Python中使用Yeast Data遇到了错误问题。为什么？

1 个答案: