在 scikit 学习中将 pandas NumPy 数组作为特征向量传递？

Question

我有一个包含 5 个不同值的向量用作样本值，标签是单个整数 0、1 或 3。当我将数组作为样本传递时，机器学习算法会起作用，但我收到这个警告。如何在不收到此警告的情况下传递特征向量？

import numpy as np
from numpy import random

from sklearn import neighbors
from sklearn.model_selection import train_test_split
import pandas as pd

filepath = 'test.csv'

# example label values
index = [0,1,3,1,1,1,0,0]

# example sample arrays
data = []
for i in range(len(index)):
    d = []
    for i in range(6):
        d.append(random.randint(50,200))
    data.append(d)

feat1 = 'brightness'
feat2, feat3, feat4 = ['h', 's', 'v']
feat5 = 'median hue'
feat6 = 'median value'

features = [feat1, feat2, feat3, feat4, feat5, feat6]

df = pd.DataFrame(data, columns=features, index=index)
df.index.name = 'state'

with open(filepath, 'a') as f:
    df.to_csv(f, header=f.tell() == 0)

states = pd.read_csv(filepath, usecols=['state'])

df_partial = pd.read_csv(filepath, usecols=features)

states = states.astype(np.float32)
states = states.values
labels = states

samples = np.array([])
for i, row in df_partial.iterrows():
    r = row.values
    samples = np.vstack((samples, r)) if samples.size else r

n_neighbors = 5

test_size = .3
labels, test_labels, samples, test_samples = train_test_split(labels, samples, test_size=test_size)
clf1 = neighbors.KNeighborsClassifier(n_neighbors, weights='distance')
clf1 = clf1.fit(samples, labels)

score1 = clf1.score(test_samples, test_labels)

print("Here's how the models performed \nknn: %d %%" %(score1 * 100))

警告：

"DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel(). clf1 = clf1.fit(samples, labels)"

sklearn documentation for fit(self, X, Y)

Answer 1

尝试替换

states = states.values 来自 states = states.values.flatten()

或

clf1 = clf1.fit(samples, labels) 来自 clf1 = clf1.fit(samples, labels.flatten())。

states = states.values 包含存储在您的熊猫数据框中的正确标签，但是它们存储在不同的行中。使用 .flatten() 将所有这些标签放在同一行。 (https://docs.scipy.org/doc/numpy-1.15.1/reference/generated/numpy.ndarray.flatten.html)

在 Sklearn 的 KNeighborsClassifier 文档中 (https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html)，他们在示例中表明标签必须存储在同一行：y = [0, 0, 1, 1].

Answer 2

当您从数据框状态检索数据时，它存储在多行（列向量）中，而它期望值在单行中。

您也可以尝试使用 ravel() 函数，该函数用于创建连续的展平数组。

numpy.ravel(array, order = ‘C’) : returns 连续扁平数组（具有所有 input-array 元素且类型相同的一维数组）

尝试：

states = states.values.ravel() 代替 states = states.values

在 scikit 学习中将 pandas NumPy 数组作为特征向量传递？

Passing pandas NumPy arrays as feature vectors in scikit learn?

pandas

scikit-learn

python-3.5