Thanks. I will give it a try.
On Friday, July 29, 2022 at 03:06:19 PM PDT, Guillaume Lemaître
<[email protected]> wrote:
You need to fit the estimator to access the fitted attribute:
In [1]: from sklearn.linear_model import RANSACRegressor ...: from
sklearn.datasets import make_regression ...: X, y = make_regression( ...:
n_samples=200, n_features=2, noise=4.0, random_state=0) ...: reg =
RANSACRegressor(random_state=0).fit(X, y)
In [2]:
In [2]: reg.inlier_mask_Out[2]: array([ True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True, True, True, True, True, True,
True, True, True, True, True])
Cheers,--Guillaume Lemaitre
Scikit-learn @ Inria Foundation
https://glemaitre.github.io/
On 29 Jul 2022, at 23:27, Shang-Rou Hsieh via scikit-learn
<[email protected]> wrote:
To whom it may concern,
Belows are the codes:
- - - - -
from sklearn.linear_model import RANSACRegressor
ransac = RANSACRegressor(LinearRegression(),
max_trials=100, # default
min_samples=0.95,
loss='absolute_error', # default
residual_threshold=None, # default
random_state=123)
inlier_mask = ransac.inlier_mask_
- - - -
Here is the error message:
AttributeError: 'RANSACRegressor' object has no attribute 'inlier_mask_'
SO I checked the attributes of RANSACRegressor using dir (RANSACRegressor) and
I do not find 'inlier_mask_'
Any advise?Henry
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