packtpublishing/python-machine-learning-cookbook

Code files for Python-Machine-Learning-Cookbook

python-machine-learning-cookbook's Issues

Chapter02/car.py returns bad input shape

Chapter02/car.py returns bad input shape with scikit-learn 0.18-2. How to fix?

-> python car.py
/usr/lib64/python2.7/site-packages/sklearn/cross_validation.py:44: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.
  "This module will be removed in 0.20.", DeprecationWarning)
Accuracy of the classifier: 78.19%
Traceback (most recent call last):
  File "car.py", line 45, in <module>
    input_data_encoded[i] = int(label_encoder[i].transform(input_data[i]))
  File "/usr/lib64/python2.7/site-packages/sklearn/preprocessing/label.py", line 143, in transform
    y = column_or_1d(y, warn=True)
  File "/usr/lib64/python2.7/site-packages/sklearn/utils/validation.py", line 562, in column_or_1d
    raise ValueError("bad input shape {0}".format(shape))
ValueError: bad input shape ()

Chapter04/vector_quantization.py, Raise ValueError: Need at least 1 and at most 32 array objects.

When I run vector_quantization.py on pthon 3, i came to this problem. How to fix it ?
Traceback (most recent call last):
File "", line 1, in
File "C:\Users\iweut\AppData\Local\Programs\Python\Python37\lib\site-packages\numpy\co
6, in _wrapfunc
return getattr(obj, method)(*args, **kwds)
ValueError: Need at least 1 and at most 32 array objects.

Chapter04/stock_market.py raise socket.gaierror

I got an socket.gaierror when I was running stock_market.py, how to fix it?

MatplotlibDeprecationWarning: The finance module has been deprecated in mpl 2.0 and will be removed in mpl 2.2. Please use the module mpl_finance instead.
  warnings.warn(message, mplDeprecation, stacklevel=1)
Traceback (most recent call last):
  File "E:\Anaconda3\lib\urllib\request.py", line 1318, in do_open
    encode_chunked=req.has_header('Transfer-encoding'))
  File "E:\Anaconda3\lib\http\client.py", line 1239, in request
    self._send_request(method, url, body, headers, encode_chunked)
  File "E:\Anaconda3\lib\http\client.py", line 1285, in _send_request
    self.endheaders(body, encode_chunked=encode_chunked)
  File "E:\Anaconda3\lib\http\client.py", line 1234, in endheaders
    self._send_output(message_body, encode_chunked=encode_chunked)
  File "E:\Anaconda3\lib\http\client.py", line 1026, in _send_output
    self.send(msg)
  File "E:\Anaconda3\lib\http\client.py", line 964, in send
    self.connect()
  File "E:\Anaconda3\lib\http\client.py", line 936, in connect
    (self.host,self.port), self.timeout, self.source_address)
  File "E:\Anaconda3\lib\socket.py", line 704, in create_connection
    for res in getaddrinfo(host, port, 0, SOCK_STREAM):
  File "E:\Anaconda3\lib\socket.py", line 745, in getaddrinfo
    for res in _socket.getaddrinfo(host, port, family, type, proto, flags):
socket.gaierror: [Errno 11001] getaddrinfo failed

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "F:/SourceCode/PythonStudy/Python-Machine-Learning-Cookbook/Chapter04/stock_market.py", line 21, in <module>
    quotes = [quotes_yahoo(symbol, start_date, end_date, asobject=True) for symbol in symbols]
  File "F:/SourceCode/PythonStudy/Python-Machine-Learning-Cookbook/Chapter04/stock_market.py", line 21, in <listcomp>
    quotes = [quotes_yahoo(symbol, start_date, end_date, asobject=True) for symbol in symbols]
  File "E:\Anaconda3\lib\site-packages\matplotlib\finance.py", line 411, in quotes_historical_yahoo_ochl
    ochl=True)
  File "E:\Anaconda3\lib\site-packages\matplotlib\finance.py", line 501, in _quotes_historical_yahoo
    fh = fetch_historical_yahoo(ticker, date1, date2, cachename)
  File "E:\Anaconda3\lib\site-packages\matplotlib\finance.py", line 360, in fetch_historical_yahoo
    with contextlib.closing(urlopen(url)) as urlfh:
  File "E:\Anaconda3\lib\urllib\request.py", line 223, in urlopen
    return opener.open(url, data, timeout)
  File "E:\Anaconda3\lib\urllib\request.py", line 526, in open
    response = self._open(req, data)
  File "E:\Anaconda3\lib\urllib\request.py", line 544, in _open
    '_open', req)
  File "E:\Anaconda3\lib\urllib\request.py", line 504, in _call_chain
    result = func(*args)
  File "E:\Anaconda3\lib\urllib\request.py", line 1346, in http_open
    return self.do_open(http.client.HTTPConnection, req)
  File "E:\Anaconda3\lib\urllib\request.py", line 1320, in do_open
    raise URLError(err)
urllib.error.URLError: <urlopen error [Errno 11001] getaddrinfo failed>

utilities module

Chapter01/bike_sharing.py

In Chapter01/bike_sharing.py, I am getting the following error:

$ python bike_sharing.py bike_day.csv
Traceback (most recent call last):
  File "bike_sharing.py", line 39, in <module>
    rf_regressor.fit(X_train, y_train)
  File "/home/BenQuigley/local_projects/machine_learning/venv/local/lib/python2.7/site-packages/sklearn/ensemble/forest.py", line 326, in fit
    for i, t in enumerate(trees))
  File "/home/BenQuigley/local_projects/machine_learning/venv/local/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.py", line 758, in __call__
    while self.dispatch_one_batch(iterator):
  File "/home/BenQuigley/local_projects/machine_learning/venv/local/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.py", line 608, in dispatch_one_batch
    self._dispatch(tasks)
  File "/home/BenQuigley/local_projects/machine_learning/venv/local/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.py", line 571, in _dispatch
    job = self._backend.apply_async(batch, callback=cb)
  File "/home/BenQuigley/local_projects/machine_learning/venv/local/lib/python2.7/site-packages/sklearn/externals/joblib/_parallel_backends.py", line 109, in apply_async
    result = ImmediateResult(func)
  File "/home/BenQuigley/local_projects/machine_learning/venv/local/lib/python2.7/site-packages/sklearn/externals/joblib/_parallel_backends.py", line 326, in __init__
    self.results = batch()
  File "/home/BenQuigley/local_projects/machine_learning/venv/local/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.py", line 131, in __call__
    return [func(*args, **kwargs) for func, args, kwargs in self.items]
  File "/home/BenQuigley/local_projects/machine_learning/venv/local/lib/python2.7/site-packages/sklearn/ensemble/forest.py", line 120, in _parallel_build_trees
    tree.fit(X, y, sample_weight=curr_sample_weight, check_input=False)
  File "/home/BenQuigley/local_projects/machine_learning/venv/local/lib/python2.7/site-packages/sklearn/tree/tree.py", line 1029, in fit
    X_idx_sorted=X_idx_sorted)
  File "/home/BenQuigley/local_projects/machine_learning/venv/local/lib/python2.7/site-packages/sklearn/tree/tree.py", line 199, in fit
    % self.min_samples_split)
ValueError: min_samples_split must be at least 2 or in (0, 1], got 1

This comes from line 37 in bike_sharing.py:

rf_regressor = RandomForestRegressor(n_estimators=1000, max_depth=10, min_samples_split=1)

Deleting the min_samples_split argument lets sklearn default it to 2, which fixes the bug. 1 is not a valid min_samples_split arg per this issue in the sklearn repo.

delete