acc defines overall accuracy
as the probability of correspondence between a positive decision
and true condition (i.e., the proportion of correct classification
decisions or of dec_cor cases).
accAn object of class numeric of length 1.
Importantly, correct decisions dec_cor
are not necessarily positive decisions dec_pos.
Understanding or obtaining the accuracy metric acc:
Definition:
acc is the (non-conditional) probability:
acc = p(dec_cor) = dec_cor/N
or the base rate (or baseline probability) of a decision being correct, but not necessarily positive.
acc values range
from 0 (no correct decision/prediction)
to 1 (perfect decision/prediction).
Computation: acc can be computed in several ways:
(a) from prob: acc = (prev x sens) + [(1 - prev) x spec]
(b) from freq: acc = dec_cor/N = (hi + cr)/(hi + mi + fa + cr)
(c) as complement of the error rate err: acc = 1 - err
When frequencies in freq are not rounded, (b) coincides with (a) and (c).
Perspective:
acc classifies a population of N individuals
by accuracy/correspondence (acc = dec_cor/N).
acc is the "by accuracy" or "by correspondence" counterpart
to prev (which adopts a "by condition" perspective) and
to ppod (which adopts a "by decision" perspective).
Alternative names: base rate of correct decisions, non-erroneous cases
In terms of frequencies,
acc is the ratio of
dec_cor (i.e., hi + cr)
divided by N (i.e.,
hi + mi + fa + cr):
acc = dec_cor/N = (hi + cr)/(hi + mi + fa + cr)
Dependencies:
acc is a feature of both the environment (true condition) and
of the decision process or diagnostic procedure. It reflects the
correspondence of decisions to conditions.
See accu for other accuracy metrics
and several possible interpretations of accuracy.
Consult Wikipedia:Accuracy_and_precision for additional information.
comp_acc computes accuracy from probabilities;
accu lists all accuracy metrics;
comp_accu_prob computes exact accuracy metrics from probabilities;
comp_accu_freq computes accuracy metrics from frequencies;
comp_sens and comp_PPV compute related probabilities;
is_extreme_prob_set verifies extreme cases;
comp_complement computes a probability's complement;
is_complement verifies probability complements;
comp_prob computes current probability information;
prob contains current probability information;
is_prob verifies probabilities.
Other probabilities:
FDR,
FOR,
NPV,
PPV,
err,
fart,
mirt,
ppod,
prev,
sens,
spec
Other metrics:
accu,
comp_accu_freq(),
comp_accu_prob(),
comp_acc(),
comp_err(),
err
acc <- .50 # sets a rate of correct decisions of 50%
acc <- 50/100 # (dec_cor) for 50 out of 100 individuals
is_prob(acc) # TRUE
#> [1] TRUE