# Classification Gains

For classification trees (those with a categorical target variable), the gain index percentage tells you how much greater the proportion of a given target category at each node differs from the overall proportion.

Node-by-Node Statistics

In this view, the table displays one row for each terminal node. For example, if the overall response to your direct mail campaign was 10% but 20% of the records that fall into node X responded positively, the index percentage for the node would be 200%, indicating that respondents in this group are twice as likely to buy relative to the overall population.

For C&R Tree and QUEST nodes where an overfit prevention set is specified, two sets of statistics are displayed:

- tree growing set - the training sample with the overfit prevention set removed
- overfit prevention set

For other C&R Tree and QUEST interactive trees, and for all CHAID interactive trees, only the tree growing set statistics are displayed.

**Nodes.** The ID of the current node (as displayed on the Viewer tab).

**Node: n.** The total number of records in that node.

**Node (%).** The percentage of all records in the dataset that fall into this node.

**Gain: n.** The number of records with the selected target category that fall into this node. In
other words, of all the records in the dataset that fall under the target category, how many are in
this node?

**Gain (%).** The percentage of all records in the target category, across the entire dataset,
that fall into this node.

**Response (%).** The percentage of records in the current node that fall under the target
category. Responses in this context are sometimes referred to as "hits."

**Index (%).** The response percentage for the current node expressed as a percentage of the
response percentage for the entire dataset. For example, an index value of 300% indicates that
records in this node are three times as likely to fall under the target category as for the dataset
as a whole.

Cumulative Statistics

In the cumulative view, the table displays one node per row, but statistics are cumulative, sorted in ascending or descending order by index percentage. For example if a descending sort is applied, the node with the highest index percentage is listed first, and statistics in the rows that follow are cumulative for that row and above.

The cumulative index percentage decreases row-by-row as nodes with lower and lower response percentages are added. The cumulative index for the final row is always 100% because at this point the entire dataset is included.

Quantiles

In this view, each row in the table represents a quantile rather than a node. The quantiles are either quartiles, quintiles (fifths), deciles (tenths), vingtiles (twentieths), or percentiles (hundredths). Multiple nodes can be listed in a single quantile if more than one node is needed to make up that percentage (for example, if quartiles are displayed but the top two nodes contain fewer than 50% of all cases). The rest of the table is cumulative and can be interpreted in the same manner as the cumulative view.