diff --git a/model_create/Results1.txt b/model_create/Results1.txt new file mode 100644 index 00000000..7643f961 --- /dev/null +++ b/model_create/Results1.txt @@ -0,0 +1,2 @@ +For this combination [['tanh', 5], ['tanh', 5], 'tanh'], R is 0.68 +The best_R for now is 0.6821 and the combination is [['tanh', 5], ['tanh', 5], 'tanh'] in 58.34 seconds \ No newline at end of file diff --git a/model_create/__pycache__/opfit.cpython-36.pyc b/model_create/__pycache__/opfit.cpython-36.pyc index 6ba7f7fb..4ec72e78 100644 Binary files a/model_create/__pycache__/opfit.cpython-36.pyc and b/model_create/__pycache__/opfit.cpython-36.pyc differ diff --git a/model_create/collection1/intermediate_output1/weights-10-0.51.hdf5 b/model_create/collection1/intermediate_output1/weights-10-0.51.hdf5 new file mode 100644 index 00000000..c87bff99 Binary files /dev/null and b/model_create/collection1/intermediate_output1/weights-10-0.51.hdf5 differ diff --git a/model_create/collection1/intermediate_output1/weights-20-0.54.hdf5 b/model_create/collection1/intermediate_output1/weights-20-0.54.hdf5 new file mode 100644 index 00000000..13b3b8ad Binary files /dev/null and b/model_create/collection1/intermediate_output1/weights-20-0.54.hdf5 differ diff --git a/model_create/latest.json b/model_create/latest.json new file mode 100644 index 00000000..bae96e90 --- /dev/null +++ b/model_create/latest.json @@ -0,0 +1 @@ +{"layer_number": 1, "starting_n": 1, "best_R": 0.6820897249614492, "best_param": [["tanh", 5], ["tanh", 5], "tanh"], "cumulative_time": 58.341623306274414} \ No newline at end of file diff --git a/model_create/opfit.py b/model_create/opfit.py index 0e98e65e..b8ae3870 100644 --- a/model_create/opfit.py +++ b/model_create/opfit.py @@ -17,7 +17,7 @@ def read_file(filename, X_var, Y_var): The function takes name of datafile, list of predictors and response it returns array_like X and Y for data fitting """ - location = os.path.abspath(filename) + location = os.path.abspath('./data/%s/'%filename) df = pd.read_csv('%s'%location,sep='\t') X = np.array(df[X_var].values) Y = np.array(df[Y_var].values)