I've been trying to implement my own dataset, but keep running into issues when using everwhereml.
I've implemented a decision tree approach using normal SKLearn and works fine.

Example using Standard Sklearn

data=pd.read_csv(config.get('Datasets', 'Minime'), delimiter=',')

# use Decision tree to classify Minime  if it is good or bad
#drop first row
data = data[['Time', 'Flag']]
data['Time'] = data['Time'].str.replace(':', '')
data['Time'] = data['Time'].str.replace('.', '')

X = data.drop('Flag', axis=1)
y = data['Flag']

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20)
classifier = DecisionTreeClassifier()
classifier.fit(X_train, y_train)

Example using everywhereml SKlearn

data=pd.read_csv(config.get('Datasets', 'Minime'), delimiter=',')

data = data[['Time', 'Flag']]
data['Time'] = data['Time'].str.replace(':', '')
data['Time'] = data['Time'].str.replace('.', '')
X = data.drop('Flag', axis=1)
y = data['Flag']
#X, y = make_blobs(n_samples=100, centers=3, n_features=2, random_state=0)

clf = DecisionTreeClassifier()

clf.fit(X, y)

Gives out this error in python3.9

Traceback (most recent call last):
  File "/home/vasilisieropoulos/gitstuff/IoT-Ai/Machine Learning/thefinish.py", line 32, in <module>
    clf.fit(X, y)
  File "/home/vasilisieropoulos/anaconda3/lib/python3.9/site-packages/everywhereml/sklearn/SklearnBaseClassifier.py", line 95, in fit
    self.dataset = Dataset.from_XY(X, y)
  File "/home/vasilisieropoulos/anaconda3/lib/python3.9/site-packages/everywhereml/data/Dataset.py", line 39, in from_XY
    return Dataset(
  File "/home/vasilisieropoulos/anaconda3/lib/python3.9/site-packages/everywhereml/data/Dataset.py", line 124, in __init__
    self.replace(X=X, y=y, feature_names=feature_names, target_names=target_names)
  File "/home/vasilisieropoulos/anaconda3/lib/python3.9/site-packages/everywhereml/data/Dataset.py", line 195, in replace
    self._update_df()
  File "/home/vasilisieropoulos/anaconda3/lib/python3.9/site-packages/everywhereml/data/Dataset.py", line 285, in _update_df
    data = np.hstack((self.X, self.y.reshape((-1, 1))))
  File "/home/vasilisieropoulos/anaconda3/lib/python3.9/site-packages/pandas/core/generic.py", line 5575, in __getattr__
    return object.__getattribute__(self, name)
AttributeError: 'Series' object has no attribute 'reshape'

Is this due to the python version or something else ? I can't get this to work in python3.10 since the Iterable abstract class was removed from collections in Python 3.10.

everywhereml/data/collect/SerialCollector.py, line 104:

AttributeError: module 'numpy' has no attribute 'int'.

np.int was a deprecated alias for the builtin int. To avoid this error in existing code, use int by itself. Doing this will not modify any behavior and is safe. When replacing np.int, you may wish to use e.g. np.int64 or np.int32 to specify the precision. If you wish to review your current use, check the release note link for additional information.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?

I suggest replacing

y=np.asarray(y, dtype=np.int),

with

y=np.asarray(y, dtype=int),

may be should add

plt.show()

after ax.imshow()

print(pipeline.to_arduino_file(filename='path-to-sketch/HogPipeline.h',instance_name='hog'
))
Traceback (most recent call last):

File "", line 1, in
print(pipeline.to_arduino_file(filename='path-to-sketch/HogPipeline.h',instance_name='hog'

File "E:\anaconda3\lib\site-packages\everywhereml\code_generators\GeneratesCode.py", line 83, in to_arduino_file
return self.to_file(filename, self.to_arduino(**kwargs))

File "E:\anaconda3\lib\site-packages\everywhereml\code_generators\GeneratesCode.py", line 74, in to_arduino
return self.to_cpp(dialect='arduino', **kwargs)

File "E:\anaconda3\lib\site-packages\everywhereml\code_generators\GeneratesCode.py", line 51, in to_cpp
return self.to_language(

File "E:\anaconda3\lib\site-packages\everywhereml\code_generators\GeneratesCode.py", line 156, in to_language
jinja = Jinja(self.template_folder, language=language, dialect=dialect)

File "E:\anaconda3\lib\site-packages\everywhereml\code_generators\jinja\Jinja.py", line 19, in init
self.loader = FileSystemLoader(base_folder, language=language, dialect=dialect)

File "E:\anaconda3\lib\site-packages\everywhereml\code_generators\jinja\FileSystemLoader.py", line 19, in init
super(FileSystemLoader, self).init(base_folder, **kwargs)

File "E:\anaconda3\lib\site-packages\jinja2\loaders.py", line 163, in init
self.searchpath = list(searchpath)

TypeError: 'WindowsPath' object is not iterable