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:
B)Do a search on a search engine about rock music=this is how she should start.
Answer:
Excite
Explanation:
The 4E framework objectives are:
EXCITE: customer are excited with relevant offer
EDUCATE: customer are educated about ongoing offers
EXPERIENCE: customer experience is improved with regards to the product
ENGAGE: customer is engaged to share feedback.
The use of location-based software application will help Jason to be excited. In this case Jason will be excited about the offer.
You get a clearer and more magnified image
Let us call x the smallest integer<span>. Because the next two </span>numbers<span> are </span>consecutive even integers<span>, we can call represent them as x + 2 and x + 4. We are told the </span>sum<span> of x, x+2, and x+4 is equal to 72. This means that the </span>integers<span> are 22, 24, and 26.</span>
