You need to write a report on how you would do Data Mining and visualizations for the three data sets. In fact we have one dataset and we have done the three projects below and now we need to write a report of 4-6 pages on how you would do Data Mining and visualizations for these 3 projects. In the case of the data visualizations this should relate to the PowerPoint presentation which is available in the like below. And there is a record for this presentation in the attachment which might also help.

Again the report should be about Data Mining and visualizations. The visualizations should have (Geographic based).

The examples that you will use inside the report should talk about the provided dataset which is the weather data in New Zealand.

Project 1: Effects of Latitude

Process the weather data for Auckland and Invercargill in the given dataset (monthly readings) and-focusing in particular on temperature related data-experiment with various data mining techniques to see if a model can be generated that predicts power consumption for these two centres. Is it easier to predict the power usage of one of these cities over the other?

Project 2: Extremes in Rainfall

Process the weather data for Christchurch and the West Coast of the South Island (as represented by Greymouth and Franz Josef) in the given dataset (hourly readings) and-focusing in particular on precipitation (i.e., rainfall) related data-experiment with various data mining techniques to see if a model can be generated that predicts power consumption for these two centres. Is it easier to predict the power usage of one of these districts over the other?

Project 3: Seasonal Effects

Process the weather data for the centres of Auckland and Hamilton in the given dataset (hourly readings) and experiment with various data mining techniques to see if a model can be generated that predicts power consumption between summer (January data) and winter (July data). Is it easier to predict the power usage for one of these seasons over the other?

The central theme to this project-shared across all the projects being run in this course-is to investigate the relationship between power usage in New Zealand, and chronological data (the time of day and the time of year) and meteorological data (the weather!) to see if any patterns exist; more specifically, to see whether the latter information helps predict the former. Each project investigates a separate aspect within this theme, applying Data Mining techniques to publically available data produced by both Transpower and the National Institute of Water and Atmospheric Research (NIWA), from which a range of visualizations will be generated.

The key steps to the project are:

1. Undertake data cleaning and processing of a rich dataset containing information that captures power consumption and climatic conditions recorded across various regions of New Zealand.

2. Feed the processed data into Weka to undertake a data modelling task.

3. Produce a set of visualizations that provide insight into the generated data

Two types of visualization will be produced: the first is focused on showing how well the predictive modelling is performing; the second is a more open-ended task, with the aim of showing "something interesting" in the data related to the project's focus. An example of "something interesting" could be a time-based geographical map showing power usage in the different regions of New Zealand enriched with what is happening in terms of temperature in the different regions.

The dataset provided for this project (also available for download through the same web site) is in the form of a set of Comma Separated Value (CSV) files. The files span a mixture of years and locations within New Zealand. While each project is different, there is one common dimension to how the data is to be used:

DI Data pertaining to the years 2011 and 2012 form the basis for training the Data Mining models;

13 Data pertaining to the year 2013 forms the basis for establishing the accuracy of the models developed.

We will now go through and detail what is involved in the three keys steps to the project. The schedule (see below) allows 1 week for each of these steps, although it should be noted there is some flexibility around this, as long as the final deadlines-a presentation and a report, due in the final week-are met. If at any point during the project you wish to go back to an earlier step and revise/adjust what you have done, this is not only permissible it is actively encouraged (!), as it reflects an increased level of understanding.