Can I do the below problem with ML?
$begingroup$
My dataset has 3 fields ColumnX, ColumnA, Column B as below.
Column X, Column_A , Column_B
AA, 1 , KEYWORD1 KEYWORD2 KEYWORD3
AA, 2 , KEYWORD4 KEYWORD5 KEYWORD6
XX, 3 , KEYWORD3 KEYWORD7
XX, 4, KEYWORD6 KEYWORD8
YY, 5, KEYWORD9
I removed the stop words in Column_B and kept the keywords.
So here Can I train a model which can classify the data with Column_X and Column_B and given an input from user which matches any keyword in Column B , returns Column_A
Sample output:
user gives an input : KEYWORD9.
my output should show ColumnX: YY and ColumnA: 5
I know it can be done with basic python but I want to use ML here
machine-learning python
asked Jan 11 at 10:18
Keshav BalivadaKeshav Balivada
1
$endgroup$
bumped to the homepage by Community♦ 11 hours ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
My dataset has 3 fields ColumnX, ColumnA, Column B as below.
Column X, Column_A , Column_B
AA, 1 , KEYWORD1 KEYWORD2 KEYWORD3
AA, 2 , KEYWORD4 KEYWORD5 KEYWORD6
XX, 3 , KEYWORD3 KEYWORD7
XX, 4, KEYWORD6 KEYWORD8
YY, 5, KEYWORD9
I removed the stop words in Column_B and kept the keywords.
So here Can I train a model which can classify the data with Column_X and Column_B and given an input from user which matches any keyword in Column B , returns Column_A
Sample output:
user gives an input : KEYWORD9.
my output should show ColumnX: YY and ColumnA: 5
I know it can be done with basic python but I want to use ML here
machine-learning python
asked Jan 11 at 10:18
Keshav BalivadaKeshav Balivada
1
$endgroup$
bumped to the homepage by Community♦ 11 hours ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
My dataset has 3 fields ColumnX, ColumnA, Column B as below.
Column X, Column_A , Column_B
AA, 1 , KEYWORD1 KEYWORD2 KEYWORD3
AA, 2 , KEYWORD4 KEYWORD5 KEYWORD6
XX, 3 , KEYWORD3 KEYWORD7
XX, 4, KEYWORD6 KEYWORD8
YY, 5, KEYWORD9
I removed the stop words in Column_B and kept the keywords.
So here Can I train a model which can classify the data with Column_X and Column_B and given an input from user which matches any keyword in Column B , returns Column_A
Sample output:
user gives an input : KEYWORD9.
my output should show ColumnX: YY and ColumnA: 5
I know it can be done with basic python but I want to use ML here
machine-learning python
asked Jan 11 at 10:18
Keshav BalivadaKeshav Balivada
1
$endgroup$
My dataset has 3 fields ColumnX, ColumnA, Column B as below.
Column X, Column_A , Column_B
AA, 1 , KEYWORD1 KEYWORD2 KEYWORD3
AA, 2 , KEYWORD4 KEYWORD5 KEYWORD6
XX, 3 , KEYWORD3 KEYWORD7
XX, 4, KEYWORD6 KEYWORD8
YY, 5, KEYWORD9
I removed the stop words in Column_B and kept the keywords.
So here Can I train a model which can classify the data with Column_X and Column_B and given an input from user which matches any keyword in Column B , returns Column_A
Sample output:
user gives an input : KEYWORD9.
my output should show ColumnX: YY and ColumnA: 5
I know it can be done with basic python but I want to use ML here
machine-learning python
machine-learning python
asked Jan 11 at 10:18
Keshav BalivadaKeshav Balivada
1
asked Jan 11 at 10:18
Keshav BalivadaKeshav Balivada
1
asked Jan 11 at 10:18
Keshav BalivadaKeshav Balivada
1
asked Jan 11 at 10:18
Keshav BalivadaKeshav Balivada
1
asked Jan 11 at 10:18
Keshav BalivadaKeshav Balivada
1
1
bumped to the homepage by Community♦ 11 hours ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
bumped to the homepage by Community♦ 11 hours ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
add a comment |
1 Answer
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$begingroup$
Try an LSTM Encoder-decoder model. The encoder takes Column_B as input and Decoder gives Column X, Column_A as output. Or create a two machine learning models one for each column prediction.
answered Jan 11 at 10:46
UdayUday
361
$endgroup$
add a comment |
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$begingroup$
Try an LSTM Encoder-decoder model. The encoder takes Column_B as input and Decoder gives Column X, Column_A as output. Or create a two machine learning models one for each column prediction.
answered Jan 11 at 10:46
UdayUday
361
$endgroup$
add a comment |
$begingroup$
Try an LSTM Encoder-decoder model. The encoder takes Column_B as input and Decoder gives Column X, Column_A as output. Or create a two machine learning models one for each column prediction.
answered Jan 11 at 10:46
UdayUday
361
$endgroup$
add a comment |
$begingroup$
Try an LSTM Encoder-decoder model. The encoder takes Column_B as input and Decoder gives Column X, Column_A as output. Or create a two machine learning models one for each column prediction.
answered Jan 11 at 10:46
UdayUday
361
$endgroup$
Try an LSTM Encoder-decoder model. The encoder takes Column_B as input and Decoder gives Column X, Column_A as output. Or create a two machine learning models one for each column prediction.
answered Jan 11 at 10:46
UdayUday
361
answered Jan 11 at 10:46
UdayUday
361
answered Jan 11 at 10:46
UdayUday
361
answered Jan 11 at 10:46
UdayUday
361
361
add a comment |
add a comment |
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