Hi,
I'm trying to use GridSearchCV and Pipeline to tune the gamma
parameter of kernel PCA. I'd like to use kernel PCA to transform the
data, followed by kmeans to cluster the data, followed by v-measure to
measure the goodness of fit of the clustering.
Here's the relevant snippet of my script
-----
# Set up the kPCA -> kmeans -> v-measure pipeline
kpca = KernelPCA(kernel="rbf")
kmeans = KMeans(n_clusters=3)
pipe = Pipeline(steps=[('kpca', kpca), ('kmeans', kmeans)])
# Range of parameters to consider for gamma in the RBF kernel for kPCA
gammas = np.logspace(-10,2,num=100)
# Parameters of pipelines are set using ‘__’ separated parameter names:
estimator = GridSearchCV(pipe, dict(kpca__gamma=gammas),
scoring=v_measure_score(labels[:,0],kmeans.labels_))
estimator.fit(D_scaled)
-----
Yet I get an AttributeError claiming that the kmeans object has no
labels_ attribute.
File "/home/lee/projects/SdA_reduce/utils/kernel_pca_pipeline.py",
line 86, in <module>
estimator = GridSearchCV(pipe, dict(kpca__gamma=gammas),
scoring=v_measure_score(labels[:,0],kmeans.labels_))
AttributeError: 'KMeans' object has no attribute 'labels_'
Does anyone have any tips on how I should restructure my snippet to
get my desired outcome?
Thanks,
Lee.
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