Data processing for machine learning using a graphical user interface
Embodiments of the present invention are directed to facilitating data preprocessing for machine learning. In accordance with aspects of the present disclosure, a training set of data is accessed. A preprocessing query specifying a set of preprocessing parameter values that indicate a manner in which to preprocess the training set of data is received. Based on the preprocessing query, a preprocessing operation is performed to preprocess the training set of data in accordance with the set of preprocessing parameter values to obtain a set of preprocessed data. The set of preprocessed data can be provided for presentation as a preview. Based on an acceptance of the set of preprocessed data, the set of preprocessed data is used to train a machine learning model that can be subsequently used to predict data.
1. A computer-implemented method comprising:
causing display of a first set of preprocessed data being generated via a first preprocessing operation that preprocesses at least a portion of an initial set of data in accordance with a first set of preprocessing parameter values that indicates a first manner in which to prepare data for subsequent use in training a machine learning model;
receiving a user selection indicating a second set of preprocessing parameter values that indicates a second manner in which to prepare the data;
causing display of a second set of preprocessed data being generated via a second preprocessing operation that preprocesses at least a portion of the first set of preprocessed data in accordance with the second set of preprocessing parameter values; and
based on an indication to train the machine learning model, using the second set of preprocessed data to train the machine learning model.
2. The computer-implemented method of claim 1 , wherein the machine learning model is used to subsequently predict data.
3. The computer-implemented method of claim 1 further comprising generating a first preprocessing query based on a user selection of the first set of preprocessing parameter values.
4. The computer-implemented method of claim 1 , wherein the first set of preprocessing parameter values includes at least one preprocessing method for use in preprocessing the at least the portion of the initial set of data.
5. The computer-implemented method of claim 1 , wherein the first set of preprocessing parameter values includes an indication of a field to preprocess.
6. The computer-implemented method of claim 1 , wherein the first preprocessing operation preprocesses the at least the portion of the initial set of data by formatting, cleaning, and/or sampling.
7. The computer-implemented method of claim 1 further comprising causing display of a display area for receiving a set of training parameter values indicating a manner in which to train the machine learning model.
8. The computer-implemented method of claim 1 further comprising receiving a set of training parameter values indicating a manner in which to train the machine learning model, the set of training parameter values including at least one of an algorithm to use for training the machine learning model, an indication of a field to predict, or an indication of a field to use for predicting.
9. The computer-implemented method of claim 1 further comprising receiving a set of training parameter values indicating a manner in which to train the machine learning model, wherein the set of training parameter values is based on a user selection of the set of training parameter values via a graphic user interface that enables concurrent user selection of the first set of preprocessing parameter values and the second set of preprocessing parameter values.
10. The computer-implemented method of claim 1 further comprising storing the first set of preprocessed data and the first set of preprocessing parameter values for subsequent use.
11. The computer-implemented method of claim 1 further comprising storing the second set of preprocessed data and the second set of preprocessing parameter values for subsequent use.
12. The computer-implemented method of claim 1 , wherein the machine learning model is trained using the second set of preprocessed data and a set of non-preprocessed data.
13. The computer-implemented method of claim 1 further comprising:
causing display of at least a portion of the first set of preprocessed data.
14. The computer-implemented method of claim 1 further comprising:
storing the second set of preprocessing parameter values;
obtaining a new training set of data;
utilizing the second set of preprocessing parameter values to perform the second preprocessing operation to preprocess the new training set of data; and
utilizing the preprocessed new training set of data to train the machine learning model.
15. The computer-implemented method of claim 1 , wherein the first set of preprocessing parameter values is different from the second set of preprocessing parameter values.
16. The computer-implemented method of claim 1 further comprising:
receiving a third set of preprocessing parameter values;
based on the third set of preprocessing parameter values, accessing the second set of preprocessed data; and
performing a third preprocessing operation to preprocess the second set of preprocessed data in accordance with the third set of preprocessing parameter values.
17. The computer-implemented method of claim 1 further comprising receiving a user selection to use the at least the portion of the second set of preprocessed data to train the machine learning model.
18. One or more computer-readable storage media having instructions stored thereon, wherein the instructions, when executed by a computing device, cause the computing device to:
causing display of a first set of preprocessed data being generated via a first preprocessing operation that preprocesses at least a portion of an initial set of data in accordance with a first set of preprocessing parameter values that indicates a first manner in which to prepare data for subsequent use in training a machine learning model;
receiving a user selection indicating a second set of preprocessing parameter values that indicates a second manner in which to prepare the data;
causing display of a second set of preprocessed data being generated via a second preprocessing operation that preprocesses at least a portion of the first set of preprocessed data in accordance with the second set of preprocessing parameter values; and
based on an indication to train the machine learning model, using the second set of preprocessed data to train the machine learning model.
19. The one or more computer-readable storage media of claim 18 , further comprising receiving a user selection to use the at least the portion of the second set of preprocessed data to train the machine learning model.
20. A computing device comprising:
one or more processors; and
a memory coupled with the one or more processors, the memory having instructions stored thereon, wherein the instructions, when executed by the one or more processors, cause the computing device to:
cause display of a first set of preprocessed data being generated via a first preprocessing operation that preprocesses at least a portion of an initial set of data in accordance with a first set of preprocessing parameter values that indicates a first manner in which to prepare data for subsequent use in training a machine learning model;
receive a user selection indicating a second set of preprocessing parameter values that indicates a second manner in which to prepare the data;
cause display of a second set of preprocessed data being generated via a second preprocessing operation that preprocesses at least a portion of the first set of preprocessed data in accordance with the second set of preprocessing parameter values; and
based on an indication to train the machine learning model, use the second set of preprocessed data to train the machine learning model.