I am currently working on a sort-of a meta-modeler to build a free web service so that people can input data and run several models on that data.
The task I am currently struggling is: user needs to enter data column by column, which would consist of a number n of ID's , a number m of attributes and a number k of classes, with the conditions that n, m > 0 and k >= 0. Data is heterogeneous, so indexes can be both numeric or text, and the same goes for attributes and classes. I'm supposing there will be no null in the data for simplicity.
I'm currently thinking on:
Creating a table with more than enough columns (all with null values), so that I can work using only the non-null columns (which will be got from user input). However this would limit the size of the datasets people could input.
Resorting to create an specialized data structure on a programming language, do all the work there and finally, create a table dinamically to store the result data there.
Using a database specialized for this kind of data (maybe a document-based DB).
Create a data structure on the RDBMS itself (I'm using PostgreSQL), let's say a variable size array, so that I can create the table directly from the user input, using only 3 variable arrays (one for indexes, one for attributes and one for classes). However, I keep in mind that attributes and indexes could be of different types, so the array would have to support heterogeneous data type and I don't know if this is possible on a RDBMS or SQL.
I've been looking for information on information but got no result until now. Any guidances to a package, language library, extension or paper, thesis, technical report with relevant information would be appreciated. Also, personal experiences with doing something similar could be useful.
Some example records:
ID NAME CODE HEIGHT WEIGHT CLASS1 CLASS2 1 HARRY 100 170 70 SURVIVOR VICTIM 2 ALBUS 101 185 82 4 REMUS 103 177 60
This is an example dataset where the intention is predicting if a person will survive or die based on its height and weight. The output should be lines consisting of SURVIVOR or VICTIM lines.
The ID's would be ID, NAME and CODE columns; HEIGHT and WEIGHT are the attributes and CLASS1 and CLASS2 are the classes.
The same structure should support something like this:
ID CODE INCOME AGE NUMBER_OF_HOUSES CHILDREN C1 C2 C3 1 101 9000 21 2 NO HIGH LOW MED 2 110 5700 30 1 YES 7 111 4000 37 0 TES
In this example, the idea is to preddict the future level of income of a person, based on it's actual age, income, number of houses and if they have children currently. The result is either HIGH, MED or LOW.
The data in this case would be: ID and CODE represent the ID's, AGE, NUMBER_OF_HOUSES, INCOME and CHILDREN represent the attributes, and C1, C2, C3 represent the classes.
The data structure should support both inputs, even though they have different number of columns for each category. And also, each one of the columns have different data type. The number of columns per category shoudn't be fixed.