ABSTRACT
In this project, we shall implement the hierarchical clustering algorithm and apply it to various data sets such as the weather data set, the student data set, and the patient data set. We shall then reduce these datasets using the following dimensionality reduction approaches: Random Projections (RP), Principal Component Analysis (PCA), Variance (Var), the New Random Approach (NRA), the Combined Approach (CA) and the Direct Approach (DA). The rand index and ARI will be implemented to measure the extent to which a given dimensionality reduction method preserves the hierarchical clustering of a data set. Finally, the six reduction methods will be compared by runtime, inter-point distance preservation, variance preservation and hierarchical clustering preservation of the original data set.
ABSTRACT
Risks are fundamentally a part of business operational models. They cannot be completely eliminated and, if not efficiently mana...
Abstract
Almajiri phenomenon is popular in Northern Nigeria due to its domination by Islamic principles as well as high...
ABSTRACT
Housing is a basic need of every human being just as food and clothing. Density simply refers to how much of a particular object...
ABSTRACT
The major aim of the study is to examine the impact of dependency on sub Saharan African devel...
ABSTRACT
The study was undertaken to investigate the effects of Periodic Testing on academic achievement of senior...
ABSTRACT
The aim of this study focused on the effects of Nigerian Pidgin English in university c...
Introduction
The relevance of science to national goals, aspirations and economy dictates to a large extent, the huge co...
ABSTRACT
Advertising has been identified as one of the factors that increase the likelihood of alcoholic beverage consum...
Background of the study
The teacher’s task is by no means easy as it involves someone who has some ideas, knowledg...
ABSTRACT
The restructuring of the electrical power industry has given rise to a high degree of vibrancy and competitive...