Difan Deng: [FIX] Numerical stability scaling for timeseries forecasting tasks (#467)

Author: Github Actions

development/_downloads/bc82bea3a5dd7bdba60b65220891d9e5/examples_python.zip

@@ -33,22 +33,22 @@ Image Classification
 
     Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz
     Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz to ../datasets/FashionMNIST/raw/train-images-idx3-ubyte.gz
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     Extracting ../datasets/FashionMNIST/raw/train-images-idx3-ubyte.gz to ../datasets/FashionMNIST/raw
 
     Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz
     Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz to ../datasets/FashionMNIST/raw/train-labels-idx1-ubyte.gz
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     Extracting ../datasets/FashionMNIST/raw/train-labels-idx1-ubyte.gz to ../datasets/FashionMNIST/raw
 
     Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz
     Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz to ../datasets/FashionMNIST/raw/t10k-images-idx3-ubyte.gz
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     Extracting ../datasets/FashionMNIST/raw/t10k-images-idx3-ubyte.gz to ../datasets/FashionMNIST/raw
 
     Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz
     Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz to ../datasets/FashionMNIST/raw/t10k-labels-idx1-ubyte.gz
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+      0%|          | 0/5148 [00:00<?, ?it/s]    100%|##########| 5148/5148 [00:00<00:00, 40586986.83it/s]
     Extracting ../datasets/FashionMNIST/raw/t10k-labels-idx1-ubyte.gz to ../datasets/FashionMNIST/raw
 
     Pipeline CS:
@@ -83,25 +83,25 @@ Image Classification
     Pipeline Random Config:
      ________________________________________ 
     Configuration(values={
-      'image_augmenter:GaussianBlur:use_augmenter': False,
-      'image_augmenter:GaussianNoise:use_augmenter': False,
-      'image_augmenter:RandomAffine:rotate': 0,
-      'image_augmenter:RandomAffine:scale_offset': 0.09817883435719255,
-      'image_augmenter:RandomAffine:shear': 3,
-      'image_augmenter:RandomAffine:translate_percent_offset': 0.092968162759446,
-      'image_augmenter:RandomAffine:use_augmenter': True,
-      'image_augmenter:RandomCutout:use_augmenter': False,
+      'image_augmenter:GaussianBlur:sigma_min': 0.40736851695519793,
+      'image_augmenter:GaussianBlur:sigma_offset': 1.9154521101106374,
+      'image_augmenter:GaussianBlur:use_augmenter': True,
+      'image_augmenter:GaussianNoise:sigma_offset': 2.1494393981863014,
+      'image_augmenter:GaussianNoise:use_augmenter': True,
+      'image_augmenter:RandomAffine:use_augmenter': False,
+      'image_augmenter:RandomCutout:p': 0.7558153204326064,
+      'image_augmenter:RandomCutout:use_augmenter': True,
       'image_augmenter:Resize:use_augmenter': True,
-      'image_augmenter:ZeroPadAndCrop:percent': 0.011876312992094795,
-      'normalizer:__choice__': 'NoNormalizer',
+      'image_augmenter:ZeroPadAndCrop:percent': 0.08168973511042621,
+      'normalizer:__choice__': 'ImageNormalizer',
     })
 
     Fitting the pipeline...
     ________________________________________
             ImageClassificationPipeline
     ________________________________________
     0-) normalizer: 
-            NoNormalizer
+            ImageNormalizer
 
     1-) preprocessing: 
             EarlyPreprocessing
@@ -173,7 +173,7 @@ Image Classification
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  6.988 seconds)
+   **Total running time of the script:** ( 0 minutes  7.417 seconds)
 
 
 .. _sphx_glr_download_examples_20_basics_example_image_classification.py:

development/_downloads/fb625db3c50d423b1b7881136ffdeec8/examples_jupyter.zip

@@ -132,7 +132,7 @@ Search for an ensemble of machine learning algorithms
  .. code-block:: none
 
 
-    <autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f494b86b6d0>
+    <autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f7f3976b6a0>
 
 
 
@@ -186,7 +186,7 @@ Print the final ensemble performance
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 5 minutes  23.914 seconds)
+   **Total running time of the script:** ( 5 minutes  20.861 seconds)
 
 
 .. _sphx_glr_download_examples_20_basics_example_tabular_classification.py:

development/_images/sphx_glr_example_plot_over_time_001.png

@@ -123,7 +123,7 @@ Search for an ensemble of machine learning algorithms
  .. code-block:: none
 
 
-    <autoPyTorch.api.tabular_regression.TabularRegressionTask object at 0x7f48bb5eeca0>
+    <autoPyTorch.api.tabular_regression.TabularRegressionTask object at 0x7f7ea94eb340>
 
 
 
@@ -163,7 +163,7 @@ Print the final ensemble performance
     |  2 | SimpleImputer,Variance Threshold,NoCoalescer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential |     0.1  |
     |  3 | None                                                                                             | LGBMLearner                                                     |     0.04 |
     autoPyTorch results:
-            Dataset name: 67f4ff2e-17dc-11ed-88b6-f144ec8da2bd
+            Dataset name: a65f386c-17ee-11ed-88a4-a98c1c8ad0eb
             Optimisation Metric: r2
             Best validation score: 0.8670098636440993
             Number of target algorithm runs: 23
@@ -179,7 +179,7 @@ Print the final ensemble performance
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 5 minutes  35.994 seconds)
+   **Total running time of the script:** ( 5 minutes  34.705 seconds)
 
 
 .. _sphx_glr_download_examples_20_basics_example_tabular_regression.py:

development/_images/sphx_glr_example_plot_over_time_thumb.png

@@ -150,7 +150,7 @@ Search for an ensemble of machine learning algorithms
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  58.007 seconds)
+   **Total running time of the script:** ( 0 minutes  57.742 seconds)
 
 
 .. _sphx_glr_download_examples_20_basics_example_time_series_forecasting.py: