dmonscilearncluster.py 文件源码

def isolationForest(self, settings, mname, data):
        '''
        :param settings: -> settings dictionary
        :param mname: -> name of serialized cluster
        :return: -> isolation forest instance
        :example settings: -> {n_estimators:100, max_samples:100, contamination:0.1, bootstrap:False,
                        max_features:1.0, n_jobs:1, random_state:None, verbose:0}
        '''
        # rng = np.random.RandomState(42)
        if settings['random_state'] == 'None':
            settings['random_state'] = None

        if isinstance(settings['bootstrap'], str):
            settings['bootstrap'] = str2Bool(settings['bootstrap'])

        if isinstance(settings['verbose'], str):
            settings['verbose'] = str2Bool(settings['verbose'])

        if settings['max_samples'] != 'auto':
            settings['max_samples'] = int(settings['max_samples'])
        # print type(settings['max_samples'])
        for k, v in settings.iteritems():
            logger.info('[%s] : [INFO] IsolationForest %s set to %s',
                         datetime.fromtimestamp(time.time()).strftime('%Y-%m-%d %H:%M:%S'), k, v)
            print "IsolationForest %s set to %s" % (k, v)
        try:
            clf = IsolationForest(n_estimators=int(settings['n_estimators']), max_samples=settings['max_samples'], contamination=float(settings['contamination']), bootstrap=settings['bootstrap'],
                        max_features=float(settings['max_features']), n_jobs=int(settings['n_jobs']), random_state=settings['random_state'], verbose=settings['verbose'])
        except Exception as inst:
            logger.error('[%s] : [ERROR] Cannot instanciate isolation forest with %s and %s',
                         datetime.fromtimestamp(time.time()).strftime('%Y-%m-%d %H:%M:%S'), type(inst), inst.args)
            print "Error while  instanciating isolation forest with %s and %s" % (type(inst), inst.args)
            sys.exit(1)
        # clf = IsolationForest(max_samples=100, random_state=rng)
        # print "*&*&*&& %s" % type(data)
        try:
            clf.fit(data)
        except Exception as inst:
            logger.error('[%s] : [ERROR] Cannot fit isolation forest model with %s and %s',
                         datetime.fromtimestamp(time.time()).strftime('%Y-%m-%d %H:%M:%S'), type(inst), inst.args)
            sys.exit(1)
        predict = clf.predict(data)
        print "Anomaly Array:"
        print predict
        self.__serializemodel(clf, 'isoforest', mname)
        return clf