According to chapter 2, the term attribute is the characteristic depending on one’s values and needs. Therefore attributes have got lots of importance depending on the characteristics set on stimulus according to the judgment.
Following data mining, it is important to note the attributes concerning the objects and attributes. Therefore the following are types of attributes:
a) Data-preprocessing-This is the type of attribute used to differentiate all the types of attributes for processing to characterize all the attributes about roles (Bogicevic, Yang, Bujisic, & Bilgihan, 2017).
c) Binary Attributes-This is the type of attribute playing the major role in the identification of values showing true or false in regards to one’s situation.
d) Ordinal Attributes-All the values are fully detected in this type of attribute according to ranks and at the same showing the basic pay scale of an individual.
Showing the difference between discrete data and Continuous data is very simple in that discrete data deals with the numerical type of data showing numbers specifying the specific data.
Continuous data entails complexity in number sequence at the same the varying data with the time frame.
Data quality is very important because it helps one make very tangible decisions when running a serious organization due to the use of high-quality data.
According to chapter 2, the transformation of raw data into the simplest format is what happens in preprocessing thus the method plays the very best role in solving the most technical errors in data mining (Hussain, Dahan, Ba-Alwib, & Ribata, 2018).
The measures between the two factors(similarity and dissimilarity are measured by the cosine of the angle determining whether the two factors are playing very important roles and even measuring the quality of the document.