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Change values from nominal to numeric

0

$begingroup$

I want to change the values of the class labels from nominal into numeric.
e.g if the values of a class are iris-setosa,iris-virginica,iris-versicolor i want to make them 0,1,2 so the instances will have as a value at the class label the form (0,0,1,2,0,1,1,2,0).
Any idea?

data-mining dataset dimensionality-reduction weka

share|improve this question

asked Nov 11 '18 at 14:57

andrikoulasandrikoulas

1

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bumped to the homepage by Community♦ 2 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 | 

0

$begingroup$

I want to change the values of the class labels from nominal into numeric.
e.g if the values of a class are iris-setosa,iris-virginica,iris-versicolor i want to make them 0,1,2 so the instances will have as a value at the class label the form (0,0,1,2,0,1,1,2,0).
Any idea?

data-mining dataset dimensionality-reduction weka

share|improve this question

asked Nov 11 '18 at 14:57

andrikoulasandrikoulas

1

$endgroup$

bumped to the homepage by Community♦ 2 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 | 

$begingroup$

I want to change the values of the class labels from nominal into numeric.
e.g if the values of a class are iris-setosa,iris-virginica,iris-versicolor i want to make them 0,1,2 so the instances will have as a value at the class label the form (0,0,1,2,0,1,1,2,0).
Any idea?

data-mining dataset dimensionality-reduction weka

share|improve this question

asked Nov 11 '18 at 14:57

andrikoulasandrikoulas

1

$endgroup$

share|improve this question

asked Nov 11 '18 at 14:57

andrikoulasandrikoulas

1

share|improve this question

asked Nov 11 '18 at 14:57

andrikoulasandrikoulas

1

asked Nov 11 '18 at 14:57

andrikoulasandrikoulas

1

asked Nov 11 '18 at 14:57

andrikoulasandrikoulas

1

1 Answer
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votes

1

$begingroup$

It's called Label Encoding

In python with the help of scikit-learn you can do following:

le = preprocessing.LabelEncoder() le.fit(["paris", "paris", "tokyo",
"amsterdam"])

list(le.classes_)

le.transform(["tokyo", "tokyo", "paris"])

list(le.inverse_transform([2, 2, 1]))

Documentation for more info: https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html

PS: Label Encoding might be responsible for unintentional ordering of possible values. I.E. model might think that nominal value with associated numerical value 2 is more important than the nominal value with associated numerical value 1. The solution is One Hot Encoding.

share|improve this answer

answered Nov 11 '18 at 15:23

PreetPreet

4435

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1

$begingroup$

It's called Label Encoding

In python with the help of scikit-learn you can do following:

le = preprocessing.LabelEncoder() le.fit(["paris", "paris", "tokyo",
"amsterdam"])

list(le.classes_)

le.transform(["tokyo", "tokyo", "paris"])

list(le.inverse_transform([2, 2, 1]))

Documentation for more info: https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html

PS: Label Encoding might be responsible for unintentional ordering of possible values. I.E. model might think that nominal value with associated numerical value 2 is more important than the nominal value with associated numerical value 1. The solution is One Hot Encoding.

share|improve this answer

answered Nov 11 '18 at 15:23

PreetPreet

4435

$endgroup$

add a comment | 

1

$begingroup$

It's called Label Encoding

In python with the help of scikit-learn you can do following:

le = preprocessing.LabelEncoder() le.fit(["paris", "paris", "tokyo",
"amsterdam"])

list(le.classes_)

le.transform(["tokyo", "tokyo", "paris"])

list(le.inverse_transform([2, 2, 1]))

Documentation for more info: https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html

PS: Label Encoding might be responsible for unintentional ordering of possible values. I.E. model might think that nominal value with associated numerical value 2 is more important than the nominal value with associated numerical value 1. The solution is One Hot Encoding.

share|improve this answer

answered Nov 11 '18 at 15:23

PreetPreet

4435

$endgroup$

add a comment | 

$begingroup$

It's called Label Encoding

In python with the help of scikit-learn you can do following:

le = preprocessing.LabelEncoder() le.fit(["paris", "paris", "tokyo",
"amsterdam"])

list(le.classes_)

le.transform(["tokyo", "tokyo", "paris"])

list(le.inverse_transform([2, 2, 1]))

Documentation for more info: https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html

PS: Label Encoding might be responsible for unintentional ordering of possible values. I.E. model might think that nominal value with associated numerical value 2 is more important than the nominal value with associated numerical value 1. The solution is One Hot Encoding.

share|improve this answer

answered Nov 11 '18 at 15:23

PreetPreet

4435

$endgroup$

share|improve this answer

answered Nov 11 '18 at 15:23

PreetPreet

4435

answered Nov 11 '18 at 15:23

PreetPreet

4435

answered Nov 11 '18 at 15:23

PreetPreet

4435