Description Usage Arguments Details Value Note See Also Examples
Default S3 method to create gains table from a vector of diagnostic score and the class of observations.
1 2 
score 
An numeric array of diagnostic score. Same as in

class 
An array of equal length of score,
containing the class of the observations. Same as in 
negref 
The reference value, same as the

ngroup 
Number of desired groups in gains table. Ignored if

breaks 
Percentiles (in percentage) at which observations
should be separated to
form groups. If specified, 
... 

gainstable
function creates gains table containing
ngroup
number of groups or buckets. The algorithm first orders
the score variable with respect to score variable. In case of tie,
it class becomes the ordering variable, keeping the positive responses first.
The algorithm calculates the ending index in each bucket as
round((length(score) / ngroup) * (1:ngroup)). Each bucket should have
at least 5 observations.
If buckets' end index are to be ended at desired level of
population, then breaks
should be specified.
If specified, it overrides ngroup
and ngroup
is ignored.
breaks
by default always includes 100. If whole number does not exist
at specified population, nearest integers are considered.
A list of class "gainstable"
. It has the following components:
Bucket 
The serial number of buckets or groups. 
Obs 
Number of observation in the group. 
CObs 
Cumulative number of observations up to the group. 
Depth 
Cumulative population depth up to the group. 
Resp 
Number of (positive) responses in the group. 
CResp 
Cumulative number of (positive) responses up to the group. 
RespRate 
(Positive) response rate in the group. 
CRespRate 
Cumulative (positive) response rate up to the group 
CCapRate 
Cumulative overall capture rate of (positive) responses up to the group. 
Lift 
Lift index in the group. Calculated as GroupResponseRate / OverallResponseRate. 
CLift 
Cumulative lift index up to the group. 
The algorithm is designed for complete cases. If NA(s) found in
either score
or class
, then removed.
gainstable.rocit
, plot.gainstable
,
rocit
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16  data("Loan")
class < Loan$Status
score < Loan$Score
# 
gtable15 < gainstable(score = score, class = class,
negref = "FP", ngroup = 15)
gtable_custom < gainstable(score = score, class = class,
negref = "FP", breaks = seq(1,100,15))
# 
print(gtable15)
print(gtable_custom)
# 
plot(gtable15)
plot(gtable_custom)
plot(gtable_custom, type = 2)
plot(gtable_custom, type = 3)

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