Systems and methods for using machine learning as a segmentation tool

A system comprising a computer having at least one processor and a non-transient storage medium storing computer readable instructions, that when executed by said at least one processor of the computer, cause the computer to perform operations comprising:

• receiving input data from a server, the input data comprising data points related to a plurality of attributes of a set of records;
• generating a user interface on a computer device configured to receive input for a set of parameters related to a generation of a decision tree containing a set of nodes, the set of parameters comprising:
• a computerized algorithm to employ in creating the decision tree;
• constraints pertaining to the algorithm selected comprising selecting the maximum number of leaf nodes if leaf-wise is selected, or selecting the maximum depth if depth-wise is selected;
• a minimum number of records to be divided into each node of the decision tree;
• and
• a set of attributes for consideration by the decision tree from the plurality of attributes contained in the input data;
• generating, using a machine learning model, an optimal decision tree containing a plurality of nodes based on the input data and the set of parameters;
• extracting a set of statistics related to the optimal decision tree, wherein the set of statistics comprises information pertaining to the plurality of nodes of the optimal decision tree and indicative of reasoning for generation of the optimal decision tree and associated efficacy metrics for each of the attributes considered;
• and
• providing, for presentation on the user interface, an interactive graphical interface concurrently depicting the optimal decision tree and the set of statistics.

A non-transitory machine-readable medium comprising instruction thereon that, when executed by a processor unit, causes the processor unit to perform operations comprising:

• receiving input data from a server, the input data comprising data points related to a plurality of attributes of a set of records;
• generating a user interface on a computer device configured to receive input for a set of parameters related to a generation of a decision tree containing a set of nodes, the set of parameters comprising:
• a computerized algorithm to employ in creating the decision tree;
• constraints pertaining to the algorithm selected comprising selecting the maximum number of leaf nodes if leaf-wise is selected, or selecting the maximum depth if depth-wise is selected;
• a minimum number of records to be divided into each node of the decision tree;
• and
• a set of attributes for consideration by the decision tree from the plurality of attributes contained in the input data;
• generating, using a machine learning model, an optimal decision tree containing a plurality of nodes based on the input data and the set of parameters;
• extracting a set of statistics related to the optimal decision tree, wherein the set of statistics comprises information pertaining to the plurality of nodes of the optimal decision tree and indicative of reasoning for generation of the optimal decision tree and associated efficacy metrics for each of the attributes considered;
• and
• providing, for presentation on the user interface, an interactive graphical interface concurrently depicting the optimal decision tree and the set of statistics.