ValueError:形状(2,2)和(4,6)未对齐:2 (dim 1) != 4 (dim 0)

Question

抱怨这一行:

log_centers = pca.inverse_transform(centers)

代码:

# TODO: Apply your clustering algorithm of choice to the reduced data 
clusterer = KMeans(n_clusters=2, random_state=0).fit(reduced_data)
# TODO: Predict the cluster for each data point
preds = clusterer.predict(reduced_data)
# TODO: Find the cluster centers
centers = clusterer.cluster_centers_
log_centers = pca.inverse_transform(centers)

数据:

log_data = np.log(data)
good_data = log_data.drop(log_data.index[outliers]).reset_index(drop = True)
pca = PCA(n_components=2)
pca = pca.fit(good_data)
reduced_data = pca.transform(good_data)
reduced_data = pd.DataFrame(reduced_data, columns = ['Dimension 1', 'Dimension 2'])

data是csv文件;标题看起来像:

    Fresh   Milk    Grocery Frozen  Detergents_Paper    Delicatessen
0   14755   899 1382    1765    56  749
1   1838    6380    2824    1218    1216    295
2   22096   3575    7041    11422   343 2564

Answer 1

问题是pca.inverse_transform()不应该把clusters作为参数。

事实上，如果你看一下文档，它应该把从PCA 获得的数据应用到你的原始数据和而不是的质心用KMeans获得。