3 CST.1.2.3.5 - PROJ 8 100 MARKS - Define a polymorphic datatype 'a ltree to represent lazy binary trees. [4 marks] (iii) Define a function inorder of type 'a ltree -> 'a seq that traverses a lazy tree in-order, returning the nodes in a lazy list. (You should define any auxiliary functions you may use. To use it, the class is extended and a specialised void add(...) method should be provided for each acceptable type. public abstract class ConstrainedArray { protected ArrayList mArray = new [4 marks] I need help with completing the following steps to execute the assignment.

To perform a data audit: Using IBM SPSS Modeler, I need to perform a data audit on the dataset using the Data Audit Node. The following fields need to be selected for the data audit: AvgHoldTime, AvgSpeedAnswer, AvgTimePhoneTalk,AvgTimePhonePerDay, AvgPercentAbandRate, AvgPercentFirstCallSuccess, and AvgCustSatScore. Take a screenshot of the audit results and place it into the PowerPoint file. Save your IBM SPSS Modeler *.str file. This file will be submitted as part of this assignment. Take note of the results, as you will summarize the findings in the PowerPoint presentation.

To perform a correlation analysis: Using R, perform a correlation analysis on the following fields: AvgHoldTime, AvgSpeedAnswer, AvgTimePhoneTalk,AvgTimePhonePerDay, AvgPercentAbandRate, AvgPercentFirstCallSuccess, and AvgCustSatScore. Export the results into an .html file. To take a screenshot of the results in the .html file and place it into the PowerPoint file. Copy all R commands used into a Word file. This file will be submitted as part of this assignment. Take note of the results, as you will summarize the findings in the PowerPoint presentation.

I need to create charts using Excel pivot tables/charts or Tableau: One or both tools can be used for this portion of the assignment. Help me with creating all necessary charts to convincingly ascertain which regions and departments are performing the best. At least four different chart types must be used to share this information. Save the Excel and Tableau files. These files will need to be submitted as part of this assignment. Take note of the results, as you will summarize the findings in the PowerPoint presentation.

PowerPoint Presentation - Help me in creating a PowerPoint presentation that summarizes the format and results of all analyses performed. how to organize the presentation according to the following:

Introduction.Objectives for each analysis.Approach or method of analysis and justification for selecting the approach or method.

Results of each analysis.Supporting graphs, charts, etc., for each analysis.Interpretation of the results for each analysis.

General conclusion of each analysis and recommendation to the organization. Discuss which region was the best performer and which department was the best performer. Provide detailed justification for your selections.

"Notes" section for each slide that includes talking points. This information should align to the results of your analyses and be reinforced by the supporting files. The main idea behind SVD-based Collaborative Filtering is to approximate the sparse user-game matrix with a rank-k matrix: RUkkVkT. k is also referred to as the number of "factors" which are represented by the columns of Uk or the rows of VkT. Complete the function below that takes in a user_game_mat and a user_idx as usual, and performs SVD-based Collaborative Filtering with num_factors and random_state. Likewise, it should return a np.ndarray (or a np.matrix) of shape (1, user_game_mat.shape[1]) that represents the predicted playtime for each game for the user at user_idx.

Hint: The idea of SVD-based Collaborative Filtering may look simple, but it may well take a while to figure out how to implement that with sklearn (unless you implement your own SVD). It might be useful to think about what data you have available, what methods are associated with sklearn's SVD and what the shapes of your inputs to those methods should be. The ideal solution uses just one line of code for making predictions.

My user_game_mat is a sparse matrix of shape (10030,74743.

The Higgs dataset has been built after monitoring the spreading processes on Twitter before, during and after the announcement of the discovery of a new particle with the features of the elusive Higgs boson on 4th July 2012.

http://snap.stanford.edu/data/higgs-twitter.htmlLinks to an external site. (Links to an external site.) (Links to an external site.)

Here are the summary statistics on the twitter data as shown in the web site.

Social Network statistics - Nodes 456626Edges 14855842Retweet Network statisticsNodes 256491Edges 328132Reply Network statistics

Nodes 38918Edges 32523Mention Network statisticsNodes 116408Edges 150818