问题描述
使用以下网站： https://scikit-learn.org/stable/auto_examples/manifold/plot_lle_digits.html#sphx-glr-auto-examples-manifold-plot-lle-digits-py https://scikit-learn.org/stable/auto_examples/manifold/plot_swissroll.html#sphx-glr-auto-examples-manifold-plot-swissroll-py
我设法在 MNIST 数据集和 swissroll 数据集上获得了 LLE，但不知何故我不知道该怎么做才能让它在 https://www.kaggle.com/manufacturingai/predicting-fraud-w-fast-ai 等外部数据集上运行。
我的尝试如下：
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
%matplotlib inline
from matplotlib import offsetbox
from sklearn import (manifold,datasets)
n_neighbors = 30
f_fontsize = 8
data = np.genfromtxt('../content/creditcard.csv',skip_header=True)
features = data[:,:3]
targets = data[:,3] # The last column is identified as the target
def plotcreditfraudfig(X,color,X_sr,err):
fig = plt.figure()
ax = fig.add_subplot(211,projection='3d')
ax.scatter(X[:,0],X[:,1],2],cmap=plt.cm.Spectral)
ax.set_title("Original data")
ax = fig.add_subplot(212)
ax.scatter(X_sr[:,X_sr[:,cmap=plt.cm.Spectral)
plt.axis('tight')
plt.xticks([]),plt.yticks([])
plt.title('Projected data')
plt.show()
clf = manifold.LocallyLinearEmbedding(n_neighbors=n_neighbors,n_components=2,method='standard')
clf.fit(X=features,y=targets)
print("Done. Reconstruction error: %g" %clf.reconstruction_error_)
X_llecf=clf.transform(X)
plot_embedding(X_llecf,"Locally Linear Embedding")
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-106-91224a1ba194> in <module>()
1 data = np.genfromtxt('../content/creditcard.csv',skip_header=True)
----> 2 features = data[:,:3]
3 targets = data[:,3] # The last column is identified as the target
4
5 clf = manifold.LocallyLinearEmbedding(n_neighbors=n_neighbors,method='standard')
IndexError: too many indices for array: array is 1-dimensional,but 2 were indexed
解决方法
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