Bug fixes #298
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Bug fixes #298
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Previously, I made a change to calculate the complexity before logging, as the complexity column was filled with zeros if we dont use the NSGA2 survival. Still, I was updating the stats after sending them to the log file. Now Im doing everything in the right order, and the log file doesnt get filled with zeros in complexity.
We also make sure complexity is calculated before returning it.
FEAT always work with minimization problems, so the previous accuracy calculation was actually correct. I added a string explaining this, and changed how we calculate it.
FEAT is designed to work with continuous class encodings, and do
not perform the transformation itself.
Instead of changing the behavior of FEAT, I think the error message
is already clear enough and the user can easily get around this
problem if the data is not as FEAT expects.
For the record, this is the new test function:
```python
def check_estimators_dtypes(name, estimator_orig):
rnd = np.random.RandomState(0)
X_train_32 = 3 * rnd.uniform(size=(20, 5)).astype(np.float32)
X_train_32 = _enforce_estimator_tags_X(estimator_orig, X_train_32)
X_train_64 = X_train_32.astype(np.float64)
X_train_int_64 = X_train_32.astype(np.int64)
X_train_int_32 = X_train_32.astype(np.int32)
y = np.array([1, 2] * 10, dtype=np.int64)
y = _enforce_estimator_tags_y(estimator_orig, y)
```
and FEAT wont work due to:
```python
self.classes_ = [int(i) for i in np.unique(np.asarray(y))]
if (any([
i != j
for i,j in zip(self.classes_, np.arange(np.max(self.classes_)))
])):
raise ValueError('y must be a contiguous set of labels from ',
'0 to n_classes. y contains the values {}'.format(
self.classes_)
)
```.
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Fixes stats being reported before updating the objectives
Previously, I made a change to force the calculation of the
complexity:
https://github.com/cavalab/feat/blob/459e021d4fbccf1ed4dfa6bc37d15aca71bfb49b/src/feat.cc#L719C2-L724
Still, I was updating the stats after sending them to the log file
(line 714).
Now I'm doing everything in the right order, and the log file doesn't
get filled with zeros in complexity.
Implements
get_complexityfor python wrapperSince I'm changing the code to report the complexity in logfile
(if complexity is specified as one of the objectives), I also thought
that would be great to individually assess the complexity of a final
model. I added this feature, so you can call
get_complexityafter fittingthe individual.
I also make sure complexity is calculated before returning it.