[scikit-learn] Issue with Sklearn.Logistic Regression
The Helmbolds
helmrp at yahoo.com
Sun Nov 1 16:53:29 EST 2020
Here's my ynp and Xnp arrays:
Print ynp
[0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
0 1 0 0 0 0 0 0 1 1 0 0 1 1 0 0 1 0 0 0 0 0 0 1 0 0 0 1 1 0 1 1 0 1 0 0 1
1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 0
1 1 1 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1
1 1 1 1 1 1 1 1 1 1 1 1]
Shape of ynp = 160
Print Xnp
[-3.00000000e+00 -2.95000000e+00 -2.90000000e+00 -2.85000000e+00
-2.80000000e+00 -2.75000000e+00 -2.70000000e+00 -2.65000000e+00
-2.60000000e+00 -2.55000000e+00 -2.50000000e+00 -2.45000000e+00
-2.40000000e+00 -2.35000000e+00 -2.30000000e+00 -2.25000000e+00
-2.20000000e+00 -2.15000000e+00 -2.10000000e+00 -2.05000000e+00
-2.00000000e+00 -1.95000000e+00 -1.90000000e+00 -1.85000000e+00
-1.80000000e+00 -1.75000000e+00 -1.70000000e+00 -1.65000000e+00
-1.60000000e+00 -1.55000000e+00 -1.50000000e+00 -1.45000000e+00
-1.40000000e+00 -1.35000000e+00 -1.30000000e+00 -1.25000000e+00
-1.20000000e+00 -1.15000000e+00 -1.10000000e+00 -1.05000000e+00
-1.00000000e+00 -9.50000000e-01 -9.00000000e-01 -8.50000000e-01
-8.00000000e-01 -7.50000000e-01 -7.00000000e-01 -6.50000000e-01
-6.00000000e-01 -5.50000000e-01 -5.00000000e-01 -4.50000000e-01
-4.00000000e-01 -3.50000000e-01 -3.00000000e-01 -2.50000000e-01
-2.00000000e-01 -1.50000000e-01 -1.00000000e-01 -5.00000000e-02
-2.28983499e-15 5.00000000e-02 1.00000000e-01 1.50000000e-01
2.00000000e-01 2.50000000e-01 3.00000000e-01 3.50000000e-01
4.00000000e-01 4.50000000e-01 5.00000000e-01 5.50000000e-01
6.00000000e-01 6.50000000e-01 7.00000000e-01 7.50000000e-01
8.00000000e-01 8.50000000e-01 9.00000000e-01 9.50000000e-01
1.00000000e+00 1.05000000e+00 1.10000000e+00 1.15000000e+00
1.20000000e+00 1.25000000e+00 1.30000000e+00 1.35000000e+00
1.40000000e+00 1.45000000e+00 1.50000000e+00 1.55000000e+00
1.60000000e+00 1.65000000e+00 1.70000000e+00 1.75000000e+00
1.80000000e+00 1.85000000e+00 1.90000000e+00 1.95000000e+00
2.00000000e+00 2.05000000e+00 2.10000000e+00 2.15000000e+00
2.20000000e+00 2.25000000e+00 2.30000000e+00 2.35000000e+00
2.40000000e+00 2.45000000e+00 2.50000000e+00 2.55000000e+00
2.60000000e+00 2.65000000e+00 2.70000000e+00 2.75000000e+00
2.80000000e+00 2.85000000e+00 2.90000000e+00 2.95000000e+00
3.00000000e+00 3.05000000e+00 3.10000000e+00 3.15000000e+00
3.20000000e+00 3.25000000e+00 3.30000000e+00 3.35000000e+00
3.40000000e+00 3.45000000e+00 3.50000000e+00 3.55000000e+00
3.60000000e+00 3.65000000e+00 3.70000000e+00 3.75000000e+00
3.80000000e+00 3.85000000e+00 3.90000000e+00 3.95000000e+00
4.00000000e+00 4.05000000e+00 4.10000000e+00 4.15000000e+00
4.20000000e+00 4.25000000e+00 4.30000000e+00 4.35000000e+00
4.40000000e+00 4.45000000e+00 4.50000000e+00 4.55000000e+00
4.60000000e+00 4.65000000e+00 4.70000000e+00 4.75000000e+00
4.80000000e+00 4.85000000e+00 4.90000000e+00 4.95000000e+00]
Shape of Xnp = 160
Press ENTER to continue =
Now Call Logistic Regression
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-3-300811cacc0b> in <module>
103
104 aprint("Now Call Logistic Regression")
--> 105 logreg = LogisticRegression.fit(Xnp, ynp)
106 aprint("Print logreg output")
107 print(logreg)
TypeError: fit() missing 1 required positional argument: 'y'
Eh!?!?
What happened???
"You won't find the right answers if you don't ask the right questions!" (Robert Helmbold, 2013)
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