Clustering sequences of data with different lengths using ngrams.

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I am trying to cluster sequences of data that have different lengths.
I am treating the element of my sequence as a word. In other words, a list is a sentence.
To be able to achive this I am thinking of extracting ngrams like my code below.
However, I keep getting following error message:
“Arguments to IMPORT must either end with ".*" or else specify a fully qualified class name: "nltk" fails this test.”
1. How can I solve this error?
2. Am I going toward right direction?
I am a novice Matlab user and I hope I am not asking too basic questions.
Following is my Matlab code:
-------------------------------------------------------
A = [1.2,1.5; 2.4,0.5; 3.2,1.5];
B = [1.0,1.0; 2.0,0; 3.0,1.0; 4.0,0.5];
C = [1.1,1.2; 2.2,1.3; 3.3,1.5];
D = [1.3,1.3; 2.1,1.4; 3.2,1.7; 4.3, 2.0];
E = [1.3,1.8; 2.3,0.4; 3.1,1.6; 4.3,0.8];
figure()
plot(A(:,1), A(:,2)) % first column is the time-values
hold on;
plot(B(:,1), B(:,2))
hold on;
plot(E(:,1), E(:,2))
figure()
plot(C(:,1), C(:,2)) % first column is the time-values
hold on;
plot(D(:,1), D(:,2))
import nltk
from nltk import ngrams
aa = A(:)'
bb = B(:)'
cc = C(:)'
dd = D(:)'
ee = E(:)'
bb = list()
bb append(str(','.join(str(e) for e in ['x' + str(e) for e in aa])))
bb append(str(','.join(str(e) for e in ['x' + str(e) for e in bb])))
bb append(str(','.join(str(e) for e in ['x' + str(e) for e in cc])))
bb append(str(','.join(str(e) for e in ['x' + str(e) for e in dd])))
bb append(str(','.join(str(e) for e in ['x' + str(e) for e in ee])))
from sklearn.feature_extraction.text import CountVectorizer
vectorizer = CountVectorizer()
X = vectorizer.fit_transform(bb)
X.toarray()

回答(1 个)

Prabhanjan Mentla
Prabhanjan Mentla 2020-3-20
NLTK is not supported in MATLAB however one can run python functions in MATLAB by following this. There is also text analytics toolbox in MATLAB which deals text data.
  1 个评论
SOPAE YI
SOPAE YI 2020-3-20
编辑:SOPAE YI 2020-3-21
Thank you so much for crrecting me, sir.
My data is not text.
I am working on spoken sentence (or an utterance) especialy, pitch of a sentence.
Can I use NLTK to cluster sequences of (pitch) data that have different lengths?

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