Preparing Data

Before using ModelArts to build a predictive analytics model, upload data to OBS.

Uploading Data to OBS

This operation uses the OBS client to upload data. For more information about how to create a bucket and upload files, see Creating a Bucket and Uploading a File.

Perform the following operations to import data to the dataset for model training and building.

1. Log in to OBS Console and create a bucket

2. Upload the local data to the OBS bucket. If you have a large amount of data, you are advised to use OBS Browser+ to upload data or folders. The uploaded data must meet the dataset requirements of the ExeML project.

Requirements on Datasets

• The name of files in a dataset consists of letters, digits, hyphens (-), and underscores (_), and the file name extension is CSV. The files cannot be stored in the root directory of an OBS bucket, but in a folder in the OBS bucket, for example, /obs-xxx/data/input.csv.

• The files are saved in CSV format. Use newline characters (\n) to separate lines and commas (,) to separate columns of the file content. The column content cannot contain special characters such as commas (,) and newline characters. The quotation marks are not supported. It is recommended that the column content consist of letters and digits.

• The number of training columns is the same. There are at least 100 different data records (a feature with different values is considered as different data) in total. The training columns cannot contain the data of the timestamp format (such as yy-mm-dd and yyyy-mm-dd). If a column has only one value, the column is considered invalid and discarded. Ensure that the dataset contains at least two valid columns except the label column. If you select continuous values for a label column, ensure that the column contains only digits and the training data has at least 25 different values. The training data CSV file cannot contain the table header. Otherwise, the training fails.

Requirements for Files Uploaded to OBS

The OBS path of the predictive analytics projects must comply with the following rules:

• The OBS path of the input data must redirect to the data files. The data files must be stored in a folder in an OBS bucket rather than the root directory of the OBS bucket, for example, /obs-xxx/data/input.csv.

• The input data must be in CSV format. The data files do not contain the table header and the number of valid data lines must be greater than 150.

Predictive Analytics File Example

Example: Predict whether customers would be interested in a time deposit based on their characteristics.

Table 1 Parameters and meanings of data sources

Parameter	Meaning	Type	Description
attr_1	Age	Integer	Age of the customer
attr_2	Occupation	String	Occupation of the customer
attr_3	Marital status	String	Marital status of the customer
attr_4	Education status	String	Education status of the customer
attr_5	Real estate	String	Real estate of the customer
attr_6	Loan	String	Loan of the customer
attr_7	Deposit	String	Deposit of the customer

Table 2 Sample data

attr_1	attr_2	attr_3	attr_4	attr_5	attr_6	attr_7
58	management	married	tertiary	yes	no	no
44	technician	single	secondary	yes	no	no
33	entrepreneur	married	secondary	yes	yes	no
47	blue-collar	married	unknown	yes	no	no
33	unknown	single	unknown	no	no	no
35	management	married	tertiary	yes	no	no

last updated: 2024-05-18 01:55