# You should have received a copy of the GNU Affero Public License
# along with this program. If not, see http://www.gnu.org/licenses.
#
# http://numenta.org/licenses/
# ----------------------------------------------------------------------
from nupic.frameworks.prediction.helpers import importBaseDescription
config = dict(
#sensorVerbosity=3,
iterationCount = 1000,
numAValues = 10,
numBValues = 10,
#encodingFieldStyleA = 'contiguous',
encodingFieldWidthA = 50,
#encodingOnBitsA = 5,
#encodingFieldStyleB = 'contiguous',
encodingFieldWidthB = 50,
#encodingOnBitsB = 5,
b0Likelihood = None,
)
mod = importBaseDescription('../base/description.py', config)
locals().update(mod.__dict__)
inputPredScore_at3 : 0.0
inputPredScore_at4 : 0.0
If we use startCell mode, we shouldn't have this problem and should get the
following scores:
inputPredScore_at1 : 1.0
inputPredScore_at2 : 0.444444444444
inputPredScore_at3 : 0.0
inputPredScore_at4 : 0.0
"""
from nupic.frameworks.prediction.helpers import importBaseDescription
config = dict(
sensorVerbosity=0,
spVerbosity=0,
tpVerbosity=0,
ppVerbosity=2,
filenameTrain='confidence/confidence3.csv',
filenameTest='confidence/confidence3.csv',
iterationCountTrain=None,
iterationCountTest=None,
trainTPRepeats=5,
trainTP=True,
)
mod = importBaseDescription('../base/description.py', config)
locals().update(mod.__dict__)
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
# See the GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see http://www.gnu.org/licenses.
#
# http://numenta.org/licenses/
# ----------------------------------------------------------------------
from nupic.frameworks.prediction.helpers import importBaseDescription
config = dict(
# sensorVerbosity=3,
iterationCount=25000,
spPeriodicStats=0,
# numAValues = 25,
# numBValues = 25,
# encodingFieldStyleA = 'contiguous',
# encodingFieldWidthA = 50,
# encodingOnBitsA = 5,
# encodingFieldStyleB = 'contiguous',
# encodingFieldWidthB = 25,
# encodingOnBitsB = 5,
b0Likelihood=None,
)
mod = importBaseDescription("../base/description.py", config)
locals().update(mod.__dict__)
