Question

In: Computer Science

A data miner wants to identify how price and advertising drive sales for the company and...

A data miner wants to identify how price and advertising drive sales for the company and wants to forecast but does not like to use algorithms. Which of the methods below represents the best solution.

        a. regression               b. Clustering               c. segmentation           d. Neural Nets

Solutions

Expert Solution

Answer:-

A data miner wants to identify how price and advertising drive sales for the company and wants to forecast but does not like to use algorithms. Which of the methods below represents the best solution

answer:-

   b. Clustering  

explanation:-

pplications of Cluster Analysis

  • Clustering analysis is broadly used in many applications such as market research, pattern recognition, data analysis, and image processing.

  • Clustering can also help marketers discover distinct groups in their customer base. And they can characterize their customer groups based on the purchasing patterns.

  • In the field of biology, it can be used to derive plant and animal taxonomies, categorize genes with similar functionalities and gain insight into structures inherent to populations.

  • Clustering also helps in identification of areas of similar land use in an earth observation database. It also helps in the identification of groups of houses in a city according to house type, value, and geographic location.

  • Clustering also helps in classifying documents on the web for information discovery.

  • Clustering is also used in outlier detection applications such as detection of credit card fraud.

  • As a data mining function, cluster analysis serves as a tool to gain insight into the distribution of data to observe characteristics of each cluster.

Requirements of Clustering in Data Mining

The following points throw light on why clustering is required in data mining −

  • Scalability − We need highly scalable clustering algorithms to deal with large databases.

  • Ability to deal with different kinds of attributes − Algorithms should be capable to be applied on any kind of data such as interval-based (numerical) data, categorical, and binary data.

  • Discovery of clusters with attribute shape − The clustering algorithm should be capable of detecting clusters of arbitrary shape. They should not be bounded to only distance measures that tend to find spherical cluster of small sizes.

  • High dimensionality − The clustering algorithm should not only be able to handle low-dimensional data but also the high dimensional space.

  • Ability to deal with noisy data − Databases contain noisy, missing or erroneous data. Some algorithms are sensitive to such data and may lead to poor quality clusters.

  • Interpretability − The clustering results should be interpretable, comprehensible, and usable.

Clustering Methods

Clustering methods can be classified into the following categories −

  • Partitioning Method
  • Hierarchical Method
  • Density-based Method
  • Grid-Based Method
  • Model-Based Method
  • Constraint-based Method

Related Solutions

After performing anomaly detection, data miner A wants to find clusters of outliers. Data miner B...
After performing anomaly detection, data miner A wants to find clusters of outliers. Data miner B claims that this does not make any sense and suggests that A re-read the definition of an anomaly. Do you think it is meaningful to cluster anomalies? Explain.
After performing anomaly detection, data miner A wants to find clusters of outliers. Data miner B...
After performing anomaly detection, data miner A wants to find clusters of outliers. Data miner B claims that this does not make any sense and suggests that A re-read the definition of an anomaly. Do you think it is meaningful to cluster anomalies? Explain.
How data and privacy concerns are changing advertising, and identify challenges associated with leveraging data, preserving...
How data and privacy concerns are changing advertising, and identify challenges associated with leveraging data, preserving privacy, and meeting data regulations such as GDPR to increase advertising effectiveness.
A chain store corporation wants study the effects of price decrease (x1, in %) and advertising expenditure increase (x2) on sales volume (y).
  A chain store corporation wants study the effects of price decrease (x1, in %) and advertising expenditure increase (x2) on sales volume (y). The corporation imposes different levels of price decrease and advertising expenditure increase on its product in stores in eight different districts of the country and measures the changes in sales volume over the next three months. A multiple regression model is used and the following output is extracted from the computer software. ANOVA   df SS...
The following set of data shows how the advertising budget affects its sales (both in millions...
The following set of data shows how the advertising budget affects its sales (both in millions of dollars): Advertising. Sales 12.5 148 3.7 55 21.6 338 60 994 37.6 541 6.1 89 16.8 126 41.2 379 Develop the equation of the simple regression line to predict sales from advertising expenditures using these data. You will need to: -Calculate the intercept and slope of the linear regression formula that relates the advertising to sales. -Calculate the value of R-squared. -Predict the...
An advertising company wants to know whether the size of an advertisement and the color of...
An advertising company wants to know whether the size of an advertisement and the color of the advertisement make a difference in the response of magazine readers. A random sample of readers shown ads of 4 different colors and 3 different sizes. Assume that the ratings follow the normal distribution. The rating is shown in the following table: Size of Ad Color of Ad Red Blue Orange Green Small 4 3 3 8 Medium 3 5 6 7 Large 6...
How to use clustering operator to figure out results of data on rapid miner Dataset from...
How to use clustering operator to figure out results of data on rapid miner Dataset from US Airline Sentiment Analysis Any help would be much appreciated! I've been stuck on this for a long time. Thanks!
Winslow Manufacturing Company has the following unit data: Sales price                              &nbsp
Winslow Manufacturing Company has the following unit data: Sales price                                                       $600.00 Direct materials                                                   250.00 Direct labor                                                         150.00 Variable overhead                                                 35.00 Fixed overhead (based on 8,000 units)                 30.00         Marketing and administrative costs:               Variable                                                                 25.00 Fixed (based on 8,000 units)                                15.00 8,000 units were produced. There were no units in beginning Finished Goods Inventory and 1,500 units in ending Finished Goods Inventory. Required: Compute the unit product using absorption costing and variable costing. Prepare an income...
A regression analysis relating a company’s sales, their advertising expenditure, price, and time resulted in the...
A regression analysis relating a company’s sales, their advertising expenditure, price, and time resulted in the following. Regression Statistics Multiple R 0.8800 R Square 0.7744 Adjusted R Square 0.7560 Standard Error 232.29 Observations 25 ANOVA df SS MS F Significance F Regression 3 53184931.86 17728310.62 328.56 0.0000 Residual 21 1133108.30 53957.54 Total 24 54318040.16 Coefficients Standard Error t Stat P-value Intercept 927.23 1229.86 0.75 0.4593 Advertising (X1) 1.02 3.09 0.33 0.7450 Price (X2) 15.61 5.62 2.78 0.0112 Time (X3) 170.53...
Please finish the following assignment in Excel Does price affect sales? Does Advertising affect sales? Are...
Please finish the following assignment in Excel Does price affect sales? Does Advertising affect sales? Are there any interaction effects between price and advertising? Show it with graph. Price Low Medium High Low 41 21 15 Adv 25 20 14 23 16 13 Medium 28 28 14 30 22 13 32 18 12 High 50 34 13 51 40 13 52 32 13
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT