0
現在、感情分析プロジェクトではtensorflowとtflearnを使用しています。私はCSVファイルで私に与えられたソーシャルメディアの投稿のデータセットを持っており、トレーニングに使うベクトルに変えようとしています。テキストの配列をベクトルに変換する
これは私が手動でこのようなことをやっている最初の試みです。私は通常、前処理済みのデータセットをインポートしています。
(14, 1)
[[ "You'd think i'd feel the worst when im alone but it gets worst when im around you"]
[ 'I took too many drugs and I passed out and started foaming at the mouth. I wish that it would have killed me but it did not. Ugh ']]
CountVectorizer(analyzer='word', binary=False, decode_error='strict',
dtype=<class 'numpy.int64'>, encoding='utf-8',
input= ...hill day at school today! Wonderful day... one... WOW WE GRADUATED TODAY FINALLY!! This isn't th...,
lowercase=True, max_df=1.0, max_features=5000, min_df=1,
ngram_range=(1, 1), preprocessor=None, stop_words=None,
strip_accents=None, token_pattern='(?u)\\b\\w\\w+\\b',
tokenizer=None, vocabulary=None)
う：私は結果を印刷するとき、私はこれを取得
import pandas as pd
import numpy
import tensorflow as tf
import tflearn
from tflearn.data_utils import to_categorical, pad_sequences
from tflearn.datasets import imdb
import keras
from sklearn.feature_extraction.text import CountVectorizer
import pickle
import csv
highschool_posts = pd.read_csv('Depression-Posts-Sentiment.xlsx-Sheet1.csv',names=["Post"],header=None,skiprows = 1)
highschool_posts
# with open()
# pickle.dump(highschool_posts,'highschool_posts.pkl')
posts = pd.DataFrame.as_matrix(highschool_posts)
print(posts.shape)
print(posts[0:2])
# print(posts)
vectorizer = CountVectorizer(input = highschool_posts,
analyzer = "word",
tokenizer = None,
preprocessor = None,
stop_words = None,
max_features =5000)
print(vectorizer)
：
現在は、ここで私は、私はGoogleの検索中に発見した資源から試したコードです誰も私がこのような外観を出すために何をしようとすることができるかについて、より良い洞察力を持っていますか？ ：
([[17, 25, 10, 406, 26, 14, 56, 61, 62, 323, 4],
[17,
10,
2,
6409,
25,
325,
7,
3161,
4,
2588,
1977,
176,
3,
26,
50,
35,
70,
1050,
395,
4],
[9846,
8681,
56,
33,
80,
113,
125,
62,
116,
4397,
5,
17,
10,
70,
284,
4,
277,
2480,
23,
92,
46,
49,
4358,
1,
31,
78,
116,
4],
[824,
69,
704,
47,
389,
8,
1373,
4,
100,
365,
1268,
8,
17,
3524,
27,
4,
573,
2433,
299,
192,
418,
194,
174,
536,
120,
8,
364,
4],
[39,
7,
69,
519,
154,
10,
42,
2,
468,
65,
5518,
31,
6,
1924,
1,
1181,
8,
210,
45,
1,
4942,
87,
15,
78,
6544,
40,
259,
1,
388,
23,
9420,
40],
[16,
117,
14,
20,
39,
7,
2,
829,
116,
74,
35,
140,
107,
3,
5,
16,
155,
126,
125,
86,
2,
286,
10,
142,
3,
26,
14,
20,
145,
6,
67,
62,
25,
40],
[16,
21,
585,
1656,
44,
2,
4640,
3111,
5,
5022,
7,
2996,
1,
3,
15,
17,
1291,
1025,
3,
8772,
5,
2002,
1433,
27,
4,
1292,
30,
48,
88,
3,
1,
3268,
1,
7315,
4],
[9435,
2605,
20,
251,
10,
59,
1388,
58,
15,
69,
358,
164,
17,
27,
4,
66,
1,
58,
2,
7886,
1168,
7,
2,
27,
24,
45,
1,
1697,
4,
16,
71,
49,
8,
79,
64,
7,
52,
4],
[16,
133,
41,
36,
179,
26,
17,
282,
49,
176,
403,
801,
403,
17,
282,
64,
49,
6,
19,
604,
1880,
1,
19,
4,
16,
117,
92,
49,
14,
75,
99,
19,
14,
20,
47,
604,
1880,
19,
4],
[17,
25,
935,
1270,
1,
1120,
15,
6,
3538,
1328,
4,
723,
18,
3,
14,
935,
6,
378,
96,
242,
24,
760,
3,
2231,
431,
4,
18,
14,
204,
22,
125,
1115,
6119,
3151,
61,
92,
213,
38,
7467,
4],
[17,
56,
45,
236,
3,
3016,
651,
1,
1038,
131,
3,
26,
14,
20,
1050,
24,
351,
474,
5,
1,
330,
323,
4,
1,
3374,
6889,
10,
2282,
3,
480,
2,
588,
7,
6,
865,
76,
5,
474,
4419,
24,
52,
687,
4],
[6,
1525,
7,
5172,
544,
1901,
24,
6,
1,
1611,
771,
4,
2,
952,
10,
960,
397,
5,
371,
3,
127,
54,
2,
889,
23,
2146,
1112,
3304,
4,
16,
63,
32,
278,
17,
21,
644,
15,
2208,
4,
1,
17,
25,
4],
[5,
16,
77,
399,
18,
4,
16,
1052,
14,
247,
328,
31,
1,
3,
5,
16,
21,
33,
1006,
14,
8,
38,
48,
62,
4,
17,
10,
167,
39,
7,
69,
2628,
4,
16,
237,
761,
18,
14,
56,
6,
460,
810,
4],
[17,
27,
1,
5,
1,
42,
6,
414,
25,
749,
15,
522,
3,
5,
2,
1,
6344,
204,
83,
8,
79,
14,
4,
6,
230,
55,
6418,
92,
87,
2,
869,
571,
933,
772,
7,
92,
260,
47,
6,
180,
5,
9536,
27,
4],
[101,
39,
21,
88,
142,
3,
16,
80,
515,
14,
6,
189,
4,
17,
39,
56,
33,
68,
1136,
6,
1801,
4,
2,
336,
21,
791,
102,
966,
206,
63,
425,
257,
804,
3,
26,
15,
2933,
8,
2,
118,
33,
2,
8998,
4],
[1,
1921,
4,
17,
56,
8,
38,
39,
7,
2,
262,
116,
16,
37,
140,
126,
4,
2,
431,
10,
7991,
3,
2,
209,
323,
35,
1307,
4,
2,
75,
169,
18,
824,
83,
164,
21,
2,
1,
5,
494,
2159,
489,
1,
4],
[49,
174,
2115,
315,
3,
17,
25,
10,
33,
6,
1410,
2602,
3,
26,
14,
2009,
24,
2460,
6057,
4,
6,
67,
67,
8404,
25,
18,
139,
33,
1,
23,
6,
564,
4,
61,
67,
62,
129,
5,
61,
398,
5874,
22,
89,
4],
[1212,
89,
107,
130,
25,
4,
370,
15,
1965,
42,
55,
1147,
246,
4,
23,
6,
503,
446,
25,
3,
67,
89,
107,
4,
131,
10,
615,
8,
8263,
4,
195,
10,
333,
277,
2730,
1165,
1,
22,
2,
1000,
24,
1,
20,
6906,
4],
[6,
180,
230,
47,
468,
8,
147,
40,
50,
35,
464,
654,
154,
26,
14,
20,
95,
4849,
24,
125,
1298,
1700,
395,
74,
10,
59,
107,
2,
25,
23,
83,
4,
1521,
76,
381,
24,
6,
67,
1037,
195,
4,
16,
1539,
515,
14,
40],
[17,
25,
10,
48,
96,
3,
14,
63,
75,
38,
1080,
8,
2,
3932,
262,
19,
230,
19,
84,
572,
1779,
833,
4,
70,
928,
482,
2,
25,
4,
98,
159,
2618,
3,
245,
77,
4,
54,
104,
32,
456,
143,
73,
31,
17,
1246,
4],
[17,
10,
39,
7,
2,
262,
116,
16,
37,
140,
126,
40,
16,
232,
14,
42,
2,
5829,
27,
1392,
5,
494,
2562,
3091,
69,
73,
4,
349,
4014,
24,
70,
1640,
2397,
1678,
4,
12,
13,
9,
11,
12,
13,
9,
11,
6964,
793,
4],
[489,
10,
625,
4,
17,
27,
1343,
61,
7,
2,
134,
544,
1848,
56,
140,
243,
4,
3685,
1646,
10,
1048,
1256,
4,
2,
3177,
35,
398,
3,
26,
22,
223,
3,
2,
306,
1486,
10,
9125,
324,
4,
34,
10,
2,
134,
3,
964,
206,
4],
[436,
2826,
193,
1,
67,
88,
4,
129,
21,
67,
62,
4,
76,
80,
6,
957,
5,
236,
1,
4,
2,
3784,
7,
578,
5,
4526,
410,
21,
2382,
4,
118,
82,
67,
1088,
5,
430,
49,
30,
109,
401,
78,
1403,
4,
67,
746,
25,
4],
[6,
1048,
653,
1,
27,
4,
6449,
3,
322,
5,
492,
101,
27,
7,
2,
172,
4,
4357,
4921,
31,
2,
1,
3480,
4,
61,
92,
56,
1080,
2,
1,
7,
2,
27,
24,
1,
20,
122,
86,
89,
3,
18,
1588,
32,
38,
6,
459,
86],
[1204,
23,
127,
366,
15,
2,
1244,
7,
106,
956,
428,
5,
406,
129,
3,
17,
27,
158,
128,
38,
309,
896,
30,
35,
307,
23,
6,
62,
4301,
23,
143,
6790,
4,
16,
63,
32,
838,
266,
178,
546,
17,
21,
6,
19,
62,
25,
4,
19]
ご協力いただければ幸いです。 ありがとう
お返事ありがとうございます。私は実際に別のSOスレッドからコードを取得し、ドキュメントを読んでいます。私が見たものから、それは私がそれをやらなければならない方法だと思った。しかし、このやり方はもっと意味をなさない。しかし、利用可能なデータがなければならないのに、出力は '（0、0）1'と思われます。 –
私も追加したチュートリアルのリンクを見てください – maxymoo