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627295 (2) [Avatar] Offline
#1
I'm trying to make sure to thoroughly read each chapter and run all the code. Fun book so far, but I'm stumbling on section 4.7.1

I see, in the last snippet of this section, the following code:
>>> X_train, X_test, y_train, y_test = train_test_split(pca_topicvectors.values, sms.spam, test_size=0.3, random_>>> lda = LDA(n_components=1)
>>> lda.fit(X_train, y_train)
LinearDiscriminantAnalysis(n_components=1, priors=None, shrinkage=None,
solver='svd', store_covariance=False, tol=0.0001)
>>> lda.score(X_test, y_test).round(3)
0.965
>>> lda = LDA(n_components=1)
>>> scores = cross_val_score(lda, pca_topicvectors, sms.spam, cv=10)
>>> "Accuracy: {:.3f} (+/-{:.3f})".format(scores.mean(), scores.std() * 2)
'Accuracy: 0.958 (+/-0.022)'

Unfortunately, I see no definition of pca_topicvectors anywhere in the code. I've got all the code for Chapter 4 running in a Jupyterlab notebook so far, but am stuck on this section.

Am i missing something simple here?
627295 (2) [Avatar] Offline
#2

I see now that the variable is defined elsewhere and I simply neglected to include this variable from section 4.4.3 into my code.

This question is resolved. Apologies for my error.