.. _randomsampling: Random Sampling --------------- .. figure:: img/RandomSampling1.png :scale: 35 % :alt: Random Sampling Widget Random Sampling Widget Create predefined subsamples. Usage ^^^^^ #. | Pick a vector dataset to subsample. You can either type the absolute path to the file or | select it from your PC (1). #. Define the number of subsamples to create (2). #. (Optional) Define a seed to initialize the random function (3). #. (Optional) Decide to keep the corresponding test part (6). #. | (Optional) Adjust the size of the training part either by typing the number (4) or adjusting | the slider (5) #. (Optional) Adjust the output location either by typing the output path or with a dialog (7). #. (Optional) Name the training dataset(s) (8). #. (Optional) Name the test dataset(s) (8) (Only if you save them). #. Create the subsample(s) (10). By defining a seed to initialize random (4) you can recreate the subsamples on a later date. You can only name the test dataset if keep the corresponding part (6) and if the size of the training part (4) is < 100 %. Sampling process ^^^^^^^^^^^^^^^^ LSAT only considers the total number of features when sampling the inventory into a training and test dataset. Input and Output ^^^^^^^^^^^^^^^^ +------------+---------------------------------------------------------------+ | Input | Vector dataset | +------------+---------------------------------------------------------------+ | Output | Vector training dataset(s) | | | | | | Naming scheme: /\*Name (8)\*_\*Nr. of subsample\*.\*ext\* | + + + | | (Optional) Test vector dataset(s) | | | | | | Naming scheme: /\*Name (9)\*_\*Nr. of subsample\*.\*ext\* | +------------+---------------------------------------------------------------+