abhishekkrthakur / mlframework Goto Github PK
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License: Apache License 2.0
https://github.com/scikit-learn-contrib/category_encoders
don't you think it will better to encode each column with his category type for the contest ?
Hi Abhishek,
I was watching your mlframework videos (thanks for them btw!) and coding along, when I saw that this repo doesn't have a license. I wanted to use this framework for some of my own projects, so I was wondering if you could add one if possible?
Hi All,
I am trying to replicate this environment in my system. I was following the steps indicated in the book. Approaching any Machine Learning Problem.
I tried running the following the command and was receiving the following error.
I have never worked with Anaconda.
It would be great if someone can help me out.
How to use CrossValidation functionality in train or predict implementation files?
At time stamp 11:14 in the youtube video: Tips N Tricks #2: Setting up development environment for machine learning, issuing the command conda env create -f environment.yml
throws the following error.
Solving environment: failed
ResolvePackageNotFound:
- python==3.7.6=h0371630_1
File "../src/train.py", line 12, in
FOLD = int(os.environ.get("FOLD"))
TypeError: int() argument must be a string, a bytes-like object or a number, not 'NoneType'
I am having this issue.
Can anyone provide any solution?
TIA
After executing this command "sh run.sh randomforest", I got the following error messages.
Traceback (most recent call last):
File "/opt/anaconda3/envs/kaggle/lib/python3.8/runpy.py", line 193, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/opt/anaconda3/envs/kaggle/lib/python3.8/runpy.py", line 86, in _run_code
exec(code, run_globals)
File "/Users/ekaratrattagan/Program/Course/machine_learning/kaggle/e01/src/train.py", line 45, in
train_df.loc[:, c] = lbl.transform(train_df[c].values.tolist())
File "/opt/anaconda3/envs/kaggle/lib/python3.8/site-packages/sklearn/preprocessing/_label.py", line 273, in transform
_, y = encode(y, uniques=self.classes, encode=True)
File "/opt/anaconda3/envs/kaggle/lib/python3.8/site-packages/sklearn/preprocessing/_label.py", line 117, in _encode
return _encode_numpy(values, uniques, encode,
File "/opt/anaconda3/envs/kaggle/lib/python3.8/site-packages/sklearn/preprocessing/_label.py", line 49, in _encode_numpy
raise ValueError("y contains previously unseen labels: %s"
ValueError: y contains previously unseen labels: [nan, nan, nan, nan, nan, nan, nan, nan, ....
I then fixed it by adding the following two lines,
train_df[c].replace(np.nan, 'NAN', inplace=True)
valid_df[c].replace(np.nan, 'NAN', inplace=True)
,after for c in train_df.columns: and before lbl = preprocessing.LabelEncoder()
in train.py
label_encoders = {}
for c in train_df.columns:
train_df[c].replace(np.nan, 'NAN', inplace=True)
valid_df[c].replace(np.nan, 'NAN', inplace=True)
lbl = preprocessing.LabelEncoder()
After that, it worked perfectly.
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