acba/elm

Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

elm's Issues

ELM Installation problem

already installed ELM
but getting this error

len() of unsized object

error while running the example:

elmk = elm.ELMKernel()
elmk.search_param(X, y, cv="kfold", of="accuracy", eval=10)
tr_set, te_set = elm.split_sets(data, training_percent=.8, perm=True)
tr_result = elmk.train(tr_set)
te_result = elmk.test(te_set)
print(te_result.get_accuracy)

error message:

`elmk
Start search

---

TypeError Traceback (most recent call last)
in
6 # to be optimized and perform 10 searching steps.
7 # best parameters will be saved inside 'elmk' object
----> 8 elmk.search_param(X, y, cv="kfold", of="accuracy", eval=10)
9
10 # split data in training and testing sets

c:\users\e580\appdata\local\programs\python\python36\lib\site-packages\elm\elmk.py in search_param(self, database, dataprocess, path_filename, save, cv, of, kf, eval)
487 num_evals=eval,
488 param_c=param_ranges[0],
--> 489 param_kernel=param_ranges[1])
490
491 elif kernel_function == "poly":

c:\users\e580\appdata\local\programs\python\python36\lib\site-packages\optunity\api.py in minimize(f, num_evals, solver_name, pmap, **kwargs)
210 solver = make_solver(**suggestion)
211 solution, details = optimize(solver, func, maximize=False, max_evals=num_evals,
--> 212 pmap=pmap)
213 return solution, details, suggestion
214

c:\users\e580\appdata\local\programs\python\python36\lib\site-packages\optunity\api.py in optimize(solver, func, maximize, max_evals, pmap)
243 time = timeit.default_timer()
244 try:
--> 245 solution, report = solver.optimize(f, maximize, pmap=pmap)
246 except fun.MaximumEvaluationsException:
247 # early stopping because maximum number of evaluations is reached

c:\users\e580\appdata\local\programs\python\python36\lib\site-packages\optunity\solvers\CMAES.py in optimize(self, f, maximize, pmap)
137 else:
138 strategy = deap.cma.Strategy(centroid=self.start.values(),
--> 139 sigma=self.sigma)
140 toolbox.register("generate", strategy.generate, Individual)
141 toolbox.register("update", strategy.update)

c:\users\e580\appdata\local\programs\python\python36\lib\site-packages\deap\cma.py in init(self, centroid, sigma, **kargs)
88 self.centroid = numpy.array(centroid)
89
---> 90 self.dim = len(self.centroid)
91 self.sigma = sigma
92 self.pc = numpy.zeros(self.dim)

TypeError: len() of unsized object

`

Could not find a version that satisfies the requirement

Could not find a version that satisfies the requirement deap==1.0.2 (from -r requirements.txt (line 2)) (from versions: 0.9.1, 0.9.2, 1.0.0rc3, 1.0.0, 1.0.1, 1.0.2.post2, 1.2.0, 1.2.1a0, 1.2.1a1, 1.2.1a2, 1.2.1b0, 1.2.1rc3, 1.2.1, 1.2.2)
No matching distribution found for deap==1.0.2 (from -r requirements.txt (line 2))

Error in example as coded in http://elm.readthedocs.io/en/latest/usage.html

No errors occours until the following statement (the loaded data matches the data set contained in the file):
elmk.search_param(data, cv="kfold", of="accuracy", eval=10)

I get the following error:

`##### Start search #####
Traceback (most recent call last):
  File "D:/elm/elm", line 18, in <module>
    elmk.search_param(data, cv="kfold", of="accuracy", eval=10)
  File "C:\Users\roberto\AppData\Local\Programs\Python\Python35\lib\site-packages\elm\elmk.py", line 489, in search_param
    param_kernel=param_ranges[1])
  File "C:\Users\roberto\AppData\Local\Programs\Python\Python35\lib\site-packages\optunity\api.py", line 212, in minimize
    pmap=pmap)
  File "C:\Users\roberto\AppData\Local\Programs\Python\Python35\lib\site-packages\optunity\api.py", line 245, in optimize
    solution, report = solver.optimize(f, maximize, pmap=pmap)
  File "C:\Users\roberto\AppData\Local\Programs\Python\Python35\lib\site-packages\optunity\solvers\CMAES.py", line 139, in optimize
    sigma=self.sigma)
  File "C:\Users\roberto\AppData\Local\Programs\Python\Python35\lib\site-packages\deap\cma.py", line 84, in __init__
    self.dim = len(self.centroid)
TypeError: len() of unsized object

Windows 10, python 3.5.2,, JetBrains PyCharm Community Edition 2016.2(64) as ide

search_param function problem

when i try to run search_param function i got this issue:

Traceback (most recent call last):
File "<pyshell#383>", line 1, in
elmk.search_param(data, cv="kfold", of="accuracy", eval=10)
File "C:\Users\abdel\AppData\Local\Programs\Python\Python37\lib\site-packages\elm\elmk.py", line 489, in search_param
param_kernel=param_ranges[1])
File "C:\Users\abdel\AppData\Local\Programs\Python\Python37\lib\site-packages\optunity\api.py", line 212, in minimize
pmap=pmap)
File "C:\Users\abdel\AppData\Local\Programs\Python\Python37\lib\site-packages\optunity\api.py", line 245, in optimize
solution, report = solver.optimize(f, maximize, pmap=pmap)
File "C:\Users\abdel\AppData\Local\Programs\Python\Python37\lib\site-packages\optunity\solvers\CMAES.py", line 163, in optimize
halloffame=hof, verbose=False)
File "C:\Users\abdel\AppData\Local\Programs\Python\Python37\lib\site-packages\deap\algorithms.py", line 487, in eaGenerateUpdate
for ind, fit in zip(population, fitnesses):
File "C:\Users\abdel\AppData\Local\Programs\Python\Python37\lib\site-packages\optunity\solvers\CMAES.py", line 156, in evaluate
individual)]))),)
File "C:\Users\abdel\AppData\Local\Programs\Python\Python37\lib\site-packages\optunity\functions.py", line 301, in wrapped_f
value = f(*args, **kwargs)
File "C:\Users\abdel\AppData\Local\Programs\Python\Python37\lib\site-packages\optunity\functions.py", line 356, in wrapped_f
return f(*args, **kwargs)
File "C:\Users\abdel\AppData\Local\Programs\Python\Python37\lib\site-packages\optunity\constraints.py", line 151, in wrapped_f
return f(*args, **kwargs)
File "C:\Users\abdel\AppData\Local\Programs\Python\Python37\lib\site-packages\optunity\constraints.py", line 129, in wrapped_f
return f(*args, **kwargs)
File "C:\Users\abdel\AppData\Local\Programs\Python\Python37\lib\site-packages\optunity\constraints.py", line 266, in func
return f(*args, **kwargs)
File "C:\Users\abdel\AppData\Local\Programs\Python\Python37\lib\site-packages\elm\elmk.py", line 426, in wrapper_1param
dataprocess=dataprocess)
File "C:\Users\abdel\AppData\Local\Programs\Python\Python37\lib\site-packages\elm\mltools.py", line 800, in kfold_cross_validation
cv_testing_error = CVError(testing_errors)
File "C:\Users\abdel\AppData\Local\Programs\Python\Python37\lib\site-packages\elm\mltools.py", line 563, in init
self.calc_metrics()
File "C:\Users\abdel\AppData\Local\Programs\Python\Python37\lib\site-packages\elm\mltools.py", line 576, in calc_metrics
fold.dict_errors[error] = fold.get(error)
File "C:\Users\abdel\AppData\Local\Programs\Python\Python37\lib\site-packages\elm\mltools.py", line 428, in get
self._calc(error, self.expected_targets, self.predicted_targets)
File "C:\Users\abdel\AppData\Local\Programs\Python\Python37\lib\site-packages\elm\mltools.py", line 358, in _calc
self.dict_errors[name] = np.count_nonzero(_a == _b) / _b.size
ZeroDivisionError: division by zero

this my code:

data= mltools.read("C:/these1.data")
elmk = elm.ELMKernel()
elmk.search_param(data, cv="kfold", of="accuracy", eval=10)

this is my data:

array([[6000, 1999],
[6196, 2000],
[7474, 2001],
[7813, 2002],
[4684, 2003],
[4933, 2004],
[5261, 2005],
[5485, 2006],
[5869, 2007],
[6155, 2008],
[6566, 2009],
[7005, 2010],
[7372, 2011],
[7631, 2012],
[7255, 2013],
[6404, 2014],
[6736, 2015],
[6414, 2016]])

Note that i have the same issue if i use ELMRandom()

TypeError: estimator should be an estimator implementing 'fit' method

code implementation

scores = cross_val_score(clf, X, y, cv=5, scoring='accuracy')

error message:

TypeError Traceback (most recent call last)
in
2 for clf, label in zip([elm1, elm2, elm3, elm4, elm5, elm6, elm7, elm8, elm9, elm10, eclf], labels):
3
--> 4 scores = cross_val_score(clf, X, y, cv=5, scoring='accuracy')
5 print("Accuracy: %0.2f (+/- %0.2f) [%s]" % (scores.mean(), scores.std(), label))

c:\users\e580\appdata\local\programs\python\python36\lib\site-packages\sklearn\utils\validation.py in inner_f(*args, **kwargs)
61 extra_args = len(args) - len(all_args)
62 if extra_args <= 0:
--> 63 return f(*args, **kwargs)
64
65 # extra_args > 0

c:\users\e580\appdata\local\programs\python\python36\lib\site-packages\sklearn\model_selection_validation.py in cross_val_score(estimator, X, y, groups, scoring, cv, n_jobs, verbose, fit_params, pre_dispatch, error_score)
441
442 # To ensure multimetric format is not supported
-> 443 scorer = check_scoring(estimator, scoring=scoring)
444
445 cv_results = cross_validate(estimator=estimator, X=X, y=y, groups=groups,

c:\users\e580\appdata\local\programs\python\python36\lib\site-packages\sklearn\utils\validation.py in inner_f(*args, **kwargs)
61 extra_args = len(args) - len(all_args)
62 if extra_args <= 0:
-> 63 return f(*args, **kwargs)
64
65 # extra_args > 0

c:\users\e580\appdata\local\programs\python\python36\lib\site-packages\sklearn\metrics_scorer.py in check_scoring(estimator, scoring, allow_none)
426 if not hasattr(estimator, 'fit'):
427 raise TypeError("estimator should be an estimator implementing "
-> 428 "'fit' method, %r was passed" % estimator)
429 if isinstance(scoring, str):
430 return get_scorer(scoring)

TypeError: estimator should be an estimator implementing 'fit' method, <elm.elmk.ELMKernel object at 0x000001E2CA30BEF0> was passed

python 3.4 issue

I have found a couple of error running the example on a python 3.4 platform.

The main difference is that in python 2.7 dictionary.values() gives a list, instead in 3.4 it is returning a view

So I found out that for fix this issue you have to modify:
-api.py file line 205 -> solution = operator.itemgetter(index)(list(f.call_log.keys()))._asdict()
-cma.py file line 82 -> solution = self.centroid = numpy.array(list(centroid))

Can you fix this error please and better check the python 3.x compatibility ??

Best regards,
Sandro

How do you save the weights of the trained ELMK model? How can you predict the class of a new sample after the training and testing has been done?

I'm unable to find a function to save the model to a file and load the model to predict class of a new sample.

ELM example code is not running in Python 3.6

I have used the following code in Python 3.6 but nothing is running
#download an example dataset from
from sklearn import datasets
data = datasets.load_iris()
iris = pd.DataFrame(data.data, columns=data.feature_names)

create a classifier

elmk = elm.ELMKernel()

search for best parameter for this dataset

define "kfold" cross-validation method, "accuracy" as a objective function

to be optimized and perform 10 searching steps.

best parameters will be saved inside 'elmk' object

elmk.search_param(iris, cv="kfold", of="accuracy", eval=10)

split data in training and testing sets

use 80% of dataset to training and shuffle data before splitting

tr_set, te_set = elm.split_sets(iris, training_percent=.8, perm=True)

#train and test

results are Error objects

tr_result = elmk.train(iris)
te_result = elmk.test(te_set)

print(te_result.get_accuracy)

problem in search_param function

i tried thies example:

`import elm

data = elm.read("C:/Users/abdel/Downloads/elmdevel/tests/data/iris.data")

elmk = elm.ELMKernel()

elmk.search_param(data, cv="kfold", of="accuracy", eval=10)

tr_set, te_set = elm.split_sets(data, training_percent=.8, perm=True)

tr_result = elmk.train(tr_set)
te_result = elmk.test(te_set)

print(te_result.get_accuracy)`

and i have this prolem:

C:\Users\abdel\PycharmProjects\Test1\venv\lib\site-packages\deap\tools_hypervolume\pyhv.py:33: ImportWarning: Falling back to the python version of hypervolume module. Expect this to be very slow.
"module. Expect this to be very slow.", ImportWarning)
elmk

Start search

Traceback (most recent call last):
File "C:/Users/abdel/PycharmProjects/Test1/test1.py", line 7, in
elmk.search_param(data, cv="kfold", of="accuracy", eval=10)
File "C:\Users\abdel\PycharmProjects\Test1\venv\lib\site-packages\elm\elmk.py", line 489, in search_param
param_kernel=param_ranges[1])
File "C:\Users\abdel\PycharmProjects\Test1\venv\lib\site-packages\optunity\api.py", line 212, in minimize
pmap=pmap)
File "C:\Users\abdel\PycharmProjects\Test1\venv\lib\site-packages\optunity\api.py", line 245, in optimize
solution, report = solver.optimize(f, maximize, pmap=pmap)
File "C:\Users\abdel\PycharmProjects\Test1\venv\lib\site-packages\optunity\solvers\CMAES.py", line 154, in optimize
halloffame=hof, verbose=False)
File "C:\Users\abdel\PycharmProjects\Test1\venv\lib\site-packages\deap\algorithms.py", line 486, in eaGenerateUpdate
fitnesses = toolbox.map(toolbox.evaluate, population)
File "C:\Users\abdel\PycharmProjects\Test1\venv\lib\site-packages\optunity\solvers\CMAES.py", line 147, in evaluate
individual)])),)
File "C:\Users\abdel\PycharmProjects\Test1\venv\lib\site-packages\optunity\functions.py", line 286, in wrapped_f
value = f(*args, **kwargs)
File "C:\Users\abdel\PycharmProjects\Test1\venv\lib\site-packages\optunity\functions.py", line 341, in wrapped_f
return f(*args, **kwargs)
File "C:\Users\abdel\PycharmProjects\Test1\venv\lib\site-packages\optunity\constraints.py", line 150, in wrapped_f
return f(*args, **kwargs)
File "C:\Users\abdel\PycharmProjects\Test1\venv\lib\site-packages\optunity\constraints.py", line 128, in wrapped_f
return f(*args, **kwargs)
File "C:\Users\abdel\PycharmProjects\Test1\venv\lib\site-packages\optunity\constraints.py", line 265, in func
return f(*args, **kwargs)
File "C:\Users\abdel\PycharmProjects\Test1\venv\lib\site-packages\elm\elmk.py", line 426, in wrapper_1param
dataprocess=dataprocess)
File "C:\Users\abdel\PycharmProjects\Test1\venv\lib\site-packages\elm\mltools.py", line 776, in kfold_cross_validation
folds.append(database[k * fold_size: (k + 1) * fold_size, :])
TypeError: slice indices must be integers or None or have an index method

Process finished with exit code 1