Functions | |
def | init |
def | is_singularity_power_of_two |
def | lm |
def | build |
def | predict |
Variables | |
dictionary | ini = {} |
cm_kernel = None |
def model_fgg-hybrid-with-rules::build | ( | i | ) |
Build model Input: { data ct_dimensions_input ct_dimensions_output desc model_name - (earth, svm) (record_data_to_file_prefix) - if !='', use this filename prefix instead of randomly generated additional_params - x1 - cuts on first axis x2 - cuts on first axis x3 - cuts on first axis } Output: { cm_return - return code >0 if error file_with_model - file with model }
Definition at line 55 of file model_fgg-hybrid-with-rules.py.
def model_fgg-hybrid-with-rules::init | ( | i | ) |
Definition at line 24 of file model_fgg-hybrid-with-rules.py.
def model_fgg-hybrid-with-rules::is_singularity_power_of_two | ( | x | ) |
Separate possible singularities (for now, power of 2) Input: x - float number Return: True if power of 2, otherwise False
Definition at line 28 of file model_fgg-hybrid-with-rules.py.
def model_fgg-hybrid-with-rules::lm | ( | x, | ||
x1, | ||||
a1, | ||||
k1 | ||||
) |
Linear model Input: x1,a1,k1 Return: linear function
Definition at line 44 of file model_fgg-hybrid-with-rules.py.
def model_fgg-hybrid-with-rules::predict | ( | i | ) |
Predict using model Input: { model_file data ct_dimensions_input (ct_dimensions_output) - for comparison desc - cM data description model_name - (earth, svm) (max_variation_percent) - for comparison, report points where variation is more than this number (default=0.2) } Output: { cm_return - return code >0 if error (rmse) - if comparison, root mean square error for predictions vs original (max_var) - list of points with variation more than max_variation_percent }
Definition at line 180 of file model_fgg-hybrid-with-rules.py.
model_fgg-hybrid-with-rules::cm_kernel = None |
Definition at line 12 of file model_fgg-hybrid-with-rules.py.
dictionary model_fgg-hybrid-with-rules::ini = {} |
Definition at line 11 of file model_fgg-hybrid-with-rules.py.