We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
I am just trying out NGB and the LinAlgError occured. It seems the matrix has a determinant of zero, according to this post https://stackoverflow.com/questions/10326015/singular-matrix-issue-with-numpy. I have attached the datasets that I used.
Code
ngb = NGBClassifier(verbose=False) ngb.fit(X_train, y_train)
Traceback
LinAlgError Traceback (most recent call last) Input In [103], in <cell line: 5>() 22 # NGBoost 23 ngb = NGBClassifier(verbose=False) ---> 24 ngb.fit(X_train, y_train) 25 y_proba = ngb.predict_proba(X_test)[:, 1] 27 # Calculate EVs and backtest with differnt EV-rankings File ~/anaconda3/lib/python3.9/site-packages/ngboost/ngboost.py:312, in NGBoost.fit(self, X, Y, X_val, Y_val, sample_weight, val_sample_weight, train_loss_monitor, val_loss_monitor, early_stopping_rounds) 310 loss_list += [train_loss_monitor(D, Y_batch, weight_batch)] 311 loss = loss_list[-1] --> 312 grads = D.grad(Y_batch, natural=self.natural_gradient) 314 proj_grad = self.fit_base(X_batch, grads, weight_batch) 315 scale = self.line_search(proj_grad, P_batch, Y_batch, weight_batch) File ~/anaconda3/lib/python3.9/site-packages/ngboost/scores.py:12, in Score.grad(self, Y, natural) 10 if natural: 11 metric = self.metric() ---> 12 grad = np.linalg.solve(metric, grad) 13 return grad File <__array_function__ internals>:5, in solve(*args, **kwargs) File ~/anaconda3/lib/python3.9/site-packages/numpy/linalg/linalg.py:393, in solve(a, b) 391 signature = 'DD->D' if isComplexType(t) else 'dd->d' 392 extobj = get_linalg_error_extobj(_raise_linalgerror_singular) --> 393 r = gufunc(a, b, signature=signature, extobj=extobj) 395 return wrap(r.astype(result_t, copy=False)) File ~/anaconda3/lib/python3.9/site-packages/numpy/linalg/linalg.py:88, in _raise_linalgerror_singular(err, flag) 87 def _raise_linalgerror_singular(err, flag): ---> 88 raise LinAlgError("Singular matrix") LinAlgError: Singular matrix
Specs OS: Ubuntu 22.04.1 LTS x86_64 Host: G7 MD Kernel: 5.15.0-53-generic Uptime: 4 hours, 38 mins Packages: 2102 (dpkg), 19 (snap) Shell: bash 5.1.16 Resolution: 1920x1080 DE: GNOME 42.5 WM: Mutter Terminal: gnome-terminal CPU: 11th Gen Intel i7-11800H (16) @ GPU: NVIDIA GeForce RTX 3050 Ti Mobi GPU: Intel TigerLake-H GT1 [UHD Grap Memory: 10436MiB / 15780MiB
Datasets y_train.csv X_train.csv
The text was updated successfully, but these errors were encountered:
try scaling each column of your predictor matrix so that values are between 0 and 1.
Sorry, something went wrong.
try scaling each column of your predictor matrix so that values are between 0 and 1. The same error still occur.
I am also experiencing a similar error, please do you solve this problem
@BD-Sengoku, try setting the natural_gradient off ngb = NGBClassifier(... natural_gradient = False .. ) as suggested at #320 (comment)
ngb = NGBClassifier(... natural_gradient = False .. )
No branches or pull requests
I am just trying out NGB and the LinAlgError occured. It seems the matrix has a determinant of zero, according to this post https://stackoverflow.com/questions/10326015/singular-matrix-issue-with-numpy. I have attached the datasets that I used.
Code
Traceback
Complete error traceback
Specs
OS: Ubuntu 22.04.1 LTS x86_64
Host: G7 MD
Kernel: 5.15.0-53-generic
Uptime: 4 hours, 38 mins
Packages: 2102 (dpkg), 19 (snap)
Shell: bash 5.1.16
Resolution: 1920x1080
DE: GNOME 42.5
WM: Mutter
Terminal: gnome-terminal
CPU: 11th Gen Intel i7-11800H (16) @
GPU: NVIDIA GeForce RTX 3050 Ti Mobi
GPU: Intel TigerLake-H GT1 [UHD Grap
Memory: 10436MiB / 15780MiB
Datasets
y_train.csv
X_train.csv
The text was updated successfully, but these errors were encountered: