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deepcfb's Issues

Extra parameters?

are there any extra parameters needed when running python3 collect_augment_data.py ? when I run it I keep getting the result
Need data for year: []

PICKS

Would you be willing to add file to show the predicted picks, I am curious to see the outcome

api_key.yaml

Hello,

Can we have an example of the api key yaml?

is this for a stathead account that needs to be created?

couple questions

  1. For the xgboost model, how long does it take to create? I have a Mac and ran it overnight, and it never finished.
  2. When interpreting the data, how would you see this outcome? Both teams have over a 90% chance of victory with the rolling median. I am not new to writing software but new to data analytics, so please bear with me if this is a simple question. Also, I am not running the data with the xgboost model as it did not finish creating overnight, so the prediction may be off. @bszek213
    image

First Command Error

Hello,

I wanted to see if this was a normal issue, I ran the first command and receive this at the end, not sure if this is expected if there's nothing to pull or not sure just want to verify ::

File "./deepCFB/collect_data.py", line 513, in <module>
    main()
  File "./deepCFB/collect_data.py", line 511, in main
    get_teams()
  File "./deepCFB/collect_data.py", line 469, in get_teams
    output = concat(final_list)
  File "./python3.10/site-packages/pandas/core/reshape/concat.py", line 372, in concat
    op = _Concatenator(
  File "./python3.10/site-packages/pandas/core/reshape/concat.py", line 429, in __init__
    raise ValueError("No objects to concatenate")
ValueError: No objects to concatenate

Initial setup.

Thanks for sharing this. I am having trouble running this with an error on the tensorflow import in the deep_learn file. Could you add to the readme what is needed for setup to get this running? @bszek213

Issue running test

I receive the following error running test

Traceback (most recent call last):
  File "./deepCFB/deep_learning_multiclass.py", line 536, in <module>
    main()
  File "./deepCFB/deep_learning_multiclass.py", line 533, in main
    deepCfbMulti().run_analysis()
  File ./deepCFB/deep_learning_multiclass.py", line 528, in run_analysis
    self.test_forecast()
  File "./deepCFB/deep_learning_multiclass.py", line 342, in test_forecast
    prediction_rolling = self.dnn_class.predict(rolling_features_2)
  File "/python3.10/site-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "/tmp/__autograph_generated_filerpi81n4p.py", line 15, in tf__predict_function
    retval_ = ag__.converted_call(ag__.ld(step_function), (ag__.ld(self), ag__.ld(iterator)), None, fscope)
ValueError: in user code:

    File "./python3.10/site-packages/keras/src/engine/training.py", line 2416, in predict_function  *
        return step_function(self, iterator)
    File "./python3.10/site-packages/keras/src/engine/training.py", line 2401, in step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    File "./python3.10/site-packages/keras/src/engine/training.py", line 2389, in run_step  **
        outputs = model.predict_step(data)
    File "./python3.10/site-packages/keras/src/engine/training.py", line 2357, in predict_step
        return self(x, training=False)
    File "./python3.10/site-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
        raise e.with_traceback(filtered_tb) from None
    File "./python3.10/site-packages/keras/src/engine/input_spec.py", line 298, in assert_input_compatibility
        raise ValueError(

    ValueError: Input 0 of layer "sequential" is incompatible with the layer: expected shape=(None, 10), found shape=(None, 18)

Error running two teams

Error on notest when running two teams

Traceback (most recent call last):
  File "./deepCFB/deep_learning_multiclass.py", line 553, in <module>
    main()
  File "./deepCFB/deep_learning_multiclass.py", line 550, in main
    deepCfbMulti().run_analysis()
  File "./deepCFB/deep_learning_multiclass.py", line 547, in run_analysis
    self.predict_teams()
  File "./deepCFB/deep_learning_multiclass.py", line 429, in predict_teams
    team_1_feature_var = team_1_df.var().sum()
  File "./python3.10/site-packages/pandas/core/generic.py", line 11401, in var
    return NDFrame.var(self, axis, skipna, ddof, numeric_only, **kwargs)
  File "./lib/python3.10/site-packages/pandas/core/generic.py", line 11125, in var
    return self._stat_function_ddof(
  File "./lib/python3.10/site-packages/pandas/core/generic.py", line 11101, in _stat_function_ddof
    return self._reduce(
  File "./lib/python3.10/site-packages/pandas/core/frame.py", line 10519, in _reduce
    res = df._mgr.reduce(blk_func)
  File "./lib/python3.10/site-packages/pandas/core/internals/managers.py", line 1534, in reduce
    nbs = blk.reduce(func)
  File "./lib/python3.10/site-packages/pandas/core/internals/blocks.py", line 339, in reduce
    result = func(self.values)
  File "./lib/python3.10/site-packages/pandas/core/frame.py", line 10482, in blk_func
    return op(values, axis=axis, skipna=skipna, **kwds)
  File "./lib/python3.10/site-packages/pandas/core/nanops.py", line 96, in _f
    return f(*args, **kwargs)
  File "./lib/python3.10/site-packages/pandas/core/nanops.py", line 158, in f
    result = alt(values, axis=axis, skipna=skipna, **kwds)
  File "./lib/python3.10/site-packages/pandas/core/nanops.py", line 1007, in nanvar
    sqr = _ensure_numeric((avg - values) ** 2)
TypeError: unsupported operand type(s) for -: 'float' and 'str'

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