Identification of Deleterious SNPs in TACR1 Gene Using Genetic Algorithm - Computational Intelligence Techniques for Comparative Genomics - page 88

…………… A k Op k V kj

A i Op i V ij

Fig. 4 Individual genome representation

Classes (Two)
Missense or Non
Missense

A
1

A
2

A
3

Fig. 5 Rule consisting of attributes

#

Fig. 6 Operator combination for the above attribute values

symbol which
indicates the absence of the value in the rule. A central mechanism in the GA is the

The absence of the attribute in the genome is represented with ' # '

tness function that plays vital role in optimizing a speci c problem.

Classi cation rule is in the form of P to Q

P Q value is the number of samples in the dataset that are satisfying antecedent

and consequent in the rule.
P value is the number of samples in the dataset that are satisfying only the ante-
cedent part in the rule.
Q value is the number of samples in the dataset that are satisfying only the ante-
cedent part in the rule.
Rule length calculation represents the number of attributes involved in rule
formation.
L is the maximum possible length of the rule (no. of attributes).
B is the length of the current rule.

˄

True Positives (TP): This refers to the positive tuples that were correctly labeled
by the classi er.

True Negatives (TN): This refers to the negative tuples that were correctly labeled
by the classi

er.
False Positives (FP): This refers to the negative tuples that were incorrectly labeled
as positive.
False Negatives (FN): This refers to the positive tuples that were mislabeled as
negative.
Sensitivity: It measures the ability of the method to identify the occurrence of
target class accurately.
Speci city: It measures the ability of the method to separate the target class.