The main is the starting point for our neural network where all the methods are called and all the variables are set so that the NN works properly.
The following are methods in the main.py explained:
something = pd.read_csv(directory + file, sep=',', names=col_names, skiprows=range(7), usecols=range(1, 11))
cvs = comma separated values pd.read_csv() = Pandas read_csv() function imports a CSV file to DataFrame format.
| Method property | Explanation |
|---|---|
| directory + file | |
| sep=',' | Delimiter to use. |
| names=col_names | List of column names to use. |
| skiprows=range(7) | Number of lines to skip (int) at the start of the file. |
| usecols=range(1, 11) | Column(s) to use as the row labels of the DataFrame |
devset_x = tr_data.to_numpy(dtype=np.float32)
Convert the DataFrame to a NumPy array. By default, the dtype of the returned array will be the common NumPy dtype of all types in the DataFrame.
| Method property | Explanation |
|---|---|
| dtype=np.float32 | The dtype to pass to numpy.asarry() |
data_trainy_1 = np.reshape(devset_y[:int(len(devset_y)*0.9), 0], (-1, 1))
Gives a new shape to an array without changing its data.
The following are other classes used in the main explained later in this file
- Model
- GridSearch
- Dense
- Dropout
- RMSProp
- GridSearch