3) In the figures shown below, there are 2 bad clusterings based on K-means. What is the main reason for the bad results and what should be done to solve the problems? 25 O Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 1 O Cluster 2 20 15 10 -10 -15 15 20 25 (a) (b)

Q: What effect on connectivity would removing the subinterfaces have?

A: If you want to completely remove the subinterface from your configuration you can simply go to…

Q: Please elaborate on the "slice and dice" method used in dimensionality reduction.

A: "Slice and dice" is a term used often in data analysis to describe an intentional procedure for…

Q: How does dimensionality reduction use "slice and dice"?

A: In data analysis, "slice and dice" often refers to a technique of dividing a complete arrangement of…

Q: Illustrate the detailed step wise construction of two (2) clusters by using data points given table…

A: Given: Illustrate the detailed step-wise construction of two(2) clusters by using data points given…

Q: Which inter-cluster similarity metric does this line represent? MIN MAX ARGMIN Group MIN Aggregated…

A: According to Bartleby Guidelines we need to answer only one question so I have answered first…

Q: What exactly does the term "clustering" mean? In the context of the mining of data, what…

A: Introduction: Clustering is the process of dividing the data in dataset into groups. Data…

Q: It is not quite obvious what BQP's connection to NP is.

A: BQP refers to a type of decision problems where the total number of potential mistakes is…

Q: Use K-mean clustering algorithm to classify the following data into 2 clusters. Individual 1 and 3…

A: ANSWER: The calculation will order the things into k gatherings of similitude. To work out that…

Q: 2. Given a table with 8 points with corresponding clusters. Determine the quality of those clusters?

A: Answer has been explained below:-

Q: Normalize and standardise are not the same thing. Provide an example of each to prove your point.

A: We need to differentiate between normalize and standardise, with example.

Q: 3. Examine the dendrogram: How many clusters seem reasonable for describing the data?

A: Dendrogram: A dendrogram is a tree-like graphic that depicts merges and splits in order. Let's how…

Q: Examine the dendrogram: How many clusters seem reasonable for describing the data?

A: If we see the dendrogram - There are 7 clusters of size 1 - a, b, c, d, e, f, g 2 clusters of size 2…

Q: If longitudinal parity is used as an error detection code, it could be able to show that the values…

A: Longitudinal parity check is an error detection technique used in data communication. It operates on…

Q: Explain what the term "normalization" means. With examples, explain 1nf 2nf 3nf and BCNF.

A: Normalization: - Normalization is a method that reduces data redundancy, inconsistency, and removes…

Q: GR 0.0022 INF 0.3720 0.0000 INT 0.2682 0.0059 WAGE 0.0226 TAXIN 0.8565 0.0016 EDU 0.1404 0.2333…

A: Can We use ARDL model for the following information? If not, what isyour suggestion for the model?…

Q: /thôn Use students Analysis dataset: 1. Aggregate the students data set by course and calculate the…

A: The answer is as follows.

Q: Distinguish between normalization and standardization. Give an example of each to back up your…

A: In the given question Normalisation is used to transform features to be on a similar…

Q: Consider database system with two tables at different two sites as follow: Site 1 ( Student Table…

A: Here's an example of an SQL query to retrieve information from the two tables at different sites…

Q: What is Sqoop-merge and explain its use?

A: Defined about Sqoop-merge and its use

Q: Explain what method can be used to determine an optimal number of data clusters in cases when this…

A: Clustering is the process of splitting a population or set of data points into many groups so that…

Q: In Top Down Integration , identify the sequence for Depth First? O a. ABCFDE Ob. АВCDFE АВCDEF Od.…

A: We have to perform DFS on the given tree and determine the possible sequence as per the given…

Q: Create a table of values for y=4(2)^(x), starting at 0 and increasing by 1 . Full explain this…

A: The given equation is y = 4(2)^x. To create a table of values for this equation, we can substitute…

Q: clusters

A: Given :- In the above question, the dataset is mention in the above given question   Need to use k…

Q: In what ways does clustering work? It's important to know what kinds of applications data mining…

A: The Answer is given below step.

Q: How does dimensionality reduction use "slice and dice"?

A: In data analysis, "slice and dice" often refers to a technique of dividing a complete arrangement of…

Q: Examine the dendrogram How cluster needed to describe the data. Need proper explanation

A: In the above diagram, the y-axis measures inter cluster distance. 12 & 21 are joined as one…

Q: Discuss three (3) types of anomalies in Tables with examples

A: In relational databases, anomalies are inconsistencies that arise due to the suboptimal organization…

Q: 1- write the schema that descibes each relation. 2- For each table, identify the primary key and the…

A:

Q: In what ways does clustering work? It's important to know what kinds of applications data mining…

A: Clustering is the method of dividing the population or data point into a number of groups such that…

Q: Question 23 (1 point) Listen You've conducted a k-means cluster analysis and in your output you have…

A: pls check the answer below

Q: Give an example of Periodic data?

A: Let's see the solution

Q: Now, exactly what does the term "clustering" mean? What kinds of applications for data mining does…

A: In the given question Clustering is the process of making a group of abstract objects into classes…

Q: So, what does it imply when we talk about the CAP theorem? How may NoSQL databases make use of this?

A: In this question we need to explain CAP theorem and need to explain how many NoSQL databases make…

Q: Just what does the term "clustering" refer to? What data mining uses does it have?

A: Introduction: With the exponential growth of data, clustering has become an important technique in…