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: 3) In the figures shown below, there are 2 bad clusterings based on K-means. What is the main reason…

A: The first example, on the left, shows that the data was poorly clustered because the initial number…

Q: 3) In the figures shown below, there are 2 bad clusterings based on K-means. What is the main reason…

A: I have answered this question in step 2.

Q: 3) In the figures shown below, there are 2 bad clusterings based on K-means. What is the main reason…

A: K-Means clustering algorithm fails to give good results when the data contains outliers, the density…

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: You can utilize the accompanying activity however many occasions as you like: select any integer…

A: Here have to determine about the Extreme Subtraction  programming problem statement.

Q: You can utilize the accompanying activity however many occasions as you like: select any integer…

A: Here have to determine about the Extreme Subtraction  programming problem statement.

Q: 7. how to find number of clusters and number of observation in each cluster

A: Cluster is the grouping of relevant data points together.  Each data point is characterized by their…

Q: Question No. 3: a) Given are the points A = (3,4), B = (4,4), C = (4,3), D = (-3,6), E = (-4,-3), F…

A: Given data is shown below: Question No. 3: a) Given are the points A = (3,4), B = (4,4), C =…

Q: Provide brief answers with supporting computations: a. Given below are clustering results of…

A: A simple quality check on the cluster is to find the difference between the proportion of items of…

Q: Suppose that the data mining task is to cluster points (with x, y/ representing location) into three…

A: Solution ::  Let's see first what is k-means algorithm ?  Answer ::  k-means is one of the simplest…

Q: the whole question is attached as a picture  Answer only the below question  E4.6g Using the set…

A: E4.6g Using the set of tables resulting from E4.6f, describe how the anomalies shown in E4.6a,…

Q: Question # 2. Clustering CLO3,4, PLO-1,2,3, C-1,3 16 Let’s suppose, there are seven data points…

A:

Q: With Birch Algorithm, cluster the following data with 3 clusters and then calculate the Centroid,…

A:

Q: Consider the dataset: {0, 4, 5, 20, 25, 39, 43, 44} Which one is a better solution: group the…

A:

Q: The table 2 comprises some data collected by students at SCI in an experiment. The students have…

A: Dear Student, According to K-Means clustering algorithm we will first find the Euclidean distance of…

Q: Draw a reachability plot for the following dataset by hand with e = 5 and minPts = 2 (Process the…

A: ##part aprint('part a).')from sklearn.cluster import DBSCANdbscan_model=DBSCAN(eps=5,…

Q: Which of the following is TRUE about the K-Means Clustering process? Check all that apply. Two most…

A: Given the Following is TRUE about the K-Means Clustering process.

Q: Determine, the number of data points in each cluster separately whose membership value is greater…

A: GIven Data Points :    A(4,4,) B(4,3) C(3,3) D(4,3) E(3,2)

Q: 4. To detect more outliers while clustering using DB Scan you can (a) increase min Pts, (b) decrease…

A: Given algortihm - DB scan eps :- it defines the points that need to be considered in a cluster. All…

Q: Consider the following one-dimensional dataset {1,2,3,5,9}. Perform k-means algorithm with 2…

A: Answer: i) It is one of the simplest unsupervised learning algorithms that solve the well known…

Q: How do you do Cluster Analysis if you have (1) nominal data and (2) ordinal data?

A: Cluster analysis is the task of grouping the data object sets in such a way that objects in the same…

Q: QUESTION 3 Time Time Gene point point Cluster 1 2 g1 o o g2 8 g3 g4 2 g5 7 Shown above is expression…

A:

Q: 14.Explain the characteristics of customers that have the following RFM scores: {11 5}, {1 5 1}, {5…

A: RFM analysis is a marketing technique used to quantitatively rank and group customers based on the…

Q: How do you do Cluster Analysis if you have nominal data?

A: check further steps for the answer :

Q: Question on information retrieval Describe how to use Hierarchical Clustering algorithm to find k…

A: How to use Hierarchical Clustering algorithm to find k clusters It is unsupervised machine learning…

Q: Give the example scenario of each of the following data mining functions that how these functions…

A: Data mining : is the extraction of meaningful data, cleaning, transformation, pattern evolution and…

Q: Define Sqoop, and why do we use Sqoop?

A: GIVEN:   Define Sqoop, and why do we use Sqoop?

Q: Clustering refers to:     a. Partitioning of the given data is carried out using some predefined…

A: d. All of the above

Q: What is hadoop pseudo cluster? for pseudo cluster model suitable to be applied in what environment?

A: Hadoop Cluster designed for storing and analyzing huge amount of data both structured and…

Q: Use single link agglomerative clustering to group the data described by the following distance…

A: Here, we have to write a solution for the above question.

Q: Design a privacy-preserving clustering method so that a data owner would be able to ask a third…

A: Design a privacy preserving clustering method so that a data owner would be able and to ask a third…

Q: What is clustering, exactly? What applications does it have in data mining?

A: Clustering is the process of dividing a collection of abstract objects into classes. A collection of…

Q: How do the concepts of Node Name and Data Node work? How does Hadoop distribute its data to storage…

A: NameNode is controller and manager of HDFS as it knows the status and the metadata of all the files…

Q: How a classification problem is different from clustering? Justify your answer with the help of an…

A: Classification problem is different from clustering in many reasons , some of them are: 1.The…

Q: Select one clustering metric and discuss how it measures the goodness of the clusters formed.

A: According to the information given :- We have to discuss one clustering metric and how it measures…

Q: Clustering was introduced as a way to speed up k nearest neighbor (kNN) classification. Is it…

A: KNN classification K-Nearest Neighborhood is one of the easiest and most widely used methods of…

Q: After learning about the k-means clustering algorithm in the big data course, some of your…

A: Answer:)

Q: 4. Use the data provided in the table Table 1. Add one more attribute, that is the average…

A: Association analysis is useful for discovering interesting relationships hidden in large data sets.…

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

A: Defined about Sqoop-merge and its use

Q: Question (5): Apply the adaptive thresholding to cluster the following gray scale intensities {40,…

A:

Q: What is lossless and lossy dimensionality reduction? Describe any one technique for lossy…

A: The Answer is in Below Steps:-

Q: What is lossless and lossy dimensionality reduction? Describe any one technique for lossy…

A: The Answer is in Below Steps:-

Q: 3. What does coefficient of overdispersion measure (hint:

A: This study is related to the response variable of interest is a count, that is, takes on…

Q: By using pairing model ( (1/...), (2/, ...) ... ) what is the solution for DFS starting from zero. 7

A: ALGORITHM FOR DFS(Depth First Search):

Q: Create a node clustering algorithm that creates node clusters for data processing; - Select a…

A: Create a node clustering algorithm that creates node clusters for data processing; - Select a…

Q: There are two programming models in Big Data Ecosystem i.e. Map Reduce and Spark, what are the…

A: Spark –  It is basically an analytics engine for large scale data processing and it is maintained by…

Q: There are two programming models in Big Data Ecosystem i.e. Map Reduce and Spark, what are the…

A: Map Reduce and Spark: Both are models in Big Data Ecosystem.   MapReduce does not support stream…

Q: There are two programming models in Big Data Ecosystem i.e. Map Reduce and Spark, What are the…

A: Spark –  it is a unified analytics engine for large scale data processing and it is maintained by…

Q: There are two programming models in Big Data Ecosystem i.e. Map Reduce and Spark, what are the…

A: Refer to step 2 for the answer.

Q: Q6. Consider the following query Q over R(A,B,C) and S(D,E,F): SELECT A,F FROM R, S WHERE C=D AND A…

A: SUMMARY: - hence we discussed all the points.