Specifications are the technical details about each hardware component
I believe the answer could be the first choice. I'm not quite sure, though
Answer:
The answer is nearest-neighbor learning.
because nearest neighbor learning is classification algorithm.
It is used to identify the sample points that are separated into different classes and to predict that the new sample point belongs to which class.
it classify the new sample point based on the distance.
for example if there are two sample points say square and circle and we assume some center point initially for square and circle and all the other points are added to the either square or circle cluster based on the distance between sample point and center point.
while the goal of decision tree is to predict the value of the target variable by learning some rules that are inferred from the features.
In decision tree training data set is given and we need to predict output of the target variable.
Explanation:
<span>When you ask the database more complex questions using comparison operators, you are conducting a query.
</span><span>The term "query" denotes a programmatic statement that is understand by a the DBMS(Database management system) that understands how to access and manipulate data within a database. </span>
