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From a code perspective, sparse convolution operations only appear in test_ forward. Does this mean that the model only trains traditional classification and regression heads? And the process shown in…
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LASSO regression is a useful technique for building sparse models and aiding in variable selection. Suggest we implement it as an alternative to the existing methods.
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currently stacking_cv_regression.py uses X, y = check_X_y(X, y, accept_sparse=['csc', 'csr']) which checks for numeric input.
However if the first layer models perform a categorical encoding it is p…
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I try the "PASTA vignette", and get a error as fowllowing:
######################## code
pbmc dense coercion: allocating vector of size 3.1 GiB
3: In .M2v(x) : sparse->dense coercion: allocati…
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**Algorithms**
* Linear Model
- [x] Ordinary Least Squared Linear Regression
- [x] Gradient Descent Linear Regression
- [x] Stochastic Gradient Descent Linear Regression
- [x] Logist…
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## Description
mxnet.ndarray.sparse.norm causes sparse fallback in CSRNDArray in 1.5.0 and master. Additionally, that the regression passed unit tests suggests deeper issues. For example, all sparse …
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The `ScalableTestSuite.Electrical.DistributionSystemDC.ScaledExperiments.DistributionSystemModelicaIndividual_N_10_M_10` model runs correctly with both the OB and NB. The model is stateless and contai…
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C code exported by porter has wrong data type for feature value as double which will cause accuracy percentage.
scikit-learn code
```
def predict(self, X, check_input=True):
"""Predi…
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error LogisticRegression
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
in
5
…
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Hi @dllussier!
My team and I have come up with a variety of classifier models from [this article](https://github.com/orgs/brainhack-school2020/teams/url) and I was wondering if you had some suggesti…