gmyrianthous

from sklearn import preprocessing
from sklearn.linear_model import LogisticRegression

# Label encoding
label_encoder = preprocessing.LabelEncoder()
train_Y = label_encoder.fit_transform(train_Y)

# Model training
clf = LogisticRegression()
clf.fit(train_X, train_Y)

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>>> import utils
>>> print(utils.multiclass.type_of_target(train_Y))
'multiclass'

gmyrianthous

from sklearn import preprocessing

label_encoder = preprocessing.LabelEncoder()
train_Y = label_encoder.fit_transform(train_Y)

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>>> import utils
>>> print(utils.multiclass.type_of_target(train_Y))
'continuous'

gmyrianthous

import numpy as np
from sklearn.linear_model import LogisticRegression

train_X = np.array([
    [100, 1.1, 0.8],  
    [200, 1.0, 6.5],  
    [150, 1.3, 7.1],  
    [120, 1.2, 3.0],  
    [100, 1.1, 4.0],  
    [150, 1.2, 6.8],

gmyrianthous

Traceback (most recent call last):
  File "test.py", line 14, in <module>
    clf.fit(train_X, train_Y)
  File "/usr/local/lib/python3.7/site-packages/sklearn/linear_model/_logistic.py", line 1347, in fit
    check_classification_targets(y)
  File "/usr/local/lib/python3.7/site-packages/sklearn/utils/multiclass.py", line 183, in check_classification_targets
    raise ValueError("Unknown label type: %r" % y_type)
ValueError: Unknown label type: 'continuous'

gmyrianthous

SELECT DISTINCT ON (customer_id) customer_id, store_id 
FROM rental_example
ORDER BY customer_id, amount;

/*
|customer_id|store_id|
|-----------|--------|
| 58        | 2      |
| 100       | 6      |
*/

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SELECT DISTINCT ON (customer_id) customer_id, store_id
FROM rental;

/*
|customer_id|store_id|
|-----------|--------|
| 58        | 2      |
| 100       | 4      |
*/

gmyrianthous

SELECT DISTINCT(customer_id), store_id
FROM rental_example;

/*
|customer_id|store_id|
|-----------|--------|
| 100       | 4      |
| 100       | 6      |
| 58        | 2      |
*/

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SELECT DISTINCT customer_id, store_id
FROM rental_example;

/*
|customer_id|store_id|
|-----------|--------|
| 100       | 4      |
| 100       | 6      |
| 58        | 2      |
*/