# Big Data: Science

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### How to Categorize Predictive Analysis Models

You have various ways to categorize the models used for predictive analytics. In general, you can sort them out by

### How to Convert Raw Data into a Predictive Analysis Matrix

Before you can extract groups of similar data items from your dataset for your predictive analysis project, you might need to represent your data in a tabular format known as a

### How to Use K-means Cluster Algorithms in Predictive Analysis

K is an input to the algorithm for predictive analysis; it stands for the number of groupings that the algorithm must extract from a dataset, expressed algebraically as

### How to Cluster by Nearest Neighbors in Predictive Analysis

Nearest Neighbors is a simple algorithm widely used in predictive analysis to cluster data by assigning an item to a cluster by determining what other items are most similar to it. A typical use of the

### Basics of User-Based Collaborative Filters in Predictive Analysis

With a user-based approach to collaborative filtering in predictive analysis, the system can calculate similarity between pairs of users by using the cosine similarity formula, a technique much like the

### How to Visualize Predictive Analysis' Raw Data

A picture is worth a thousand words — especially when you're trying to get a good handle on your predictive analysis data. At the pre-processing step, while you're preparing your data, it's a common practice

### Basics of Data Clusters in Predictive Analysis

A dataset (or data collection) is a set of items in predictive analysis. For instance, a set of documents is a dataset where the data items are documents. A set of social network users’ information

### How to Utilize Bird Flock Clusters in Predictive Analysis

Imagine birds' flocking behavior as a model for your company's predictive analysis data. Each data item corresponds to a single bird in the flock; an appropriate visual application can show the flock in

### How to Apply Any Colony Clusters in Predictive Analysis

A natural example of self-organizing group you can apply in predictive analysis behavior is a colony of ants hunting for food. The ants collectively optimize their track so that it always takes the shortest

### How to Use Predictive Analysis Decision Trees to Predict the Future

A decision tree is an approach to predictive analysis that can help you make decisions. Suppose, for example, that you need to decide whether to invest a certain amount of money in one of three business

### How Support Vector Machine Predictive Analysis Predicts the Future

The support vector machine (SVM) is a predictive analysis data-classification algorithm that assigns new data elements to one of labeled categories. SVM is, in most cases, a

### How Predictive Analysis Neural Networks Work

A complex algorithm used for predictive analysis, the neural network, is biologically inspired by the structure of the human brain. A neural network provides a very simple model in comparison to the human

### How to Use Item-Based Collaborative Filters in Predictive Analysis

One of Amazon’s recommender systems for predictive analysis uses item-based collaborative filtering — doling out a huge inventory of products from the company database when a user views a single item on

### Basics of Major Technological Trends in Predictive Analytics

Traditional predictive analytical techniques can only provide insights on the basis of historical data. Your data — both past and incoming — can provide you with a reliable predictor that can help you

### How to Use Apache Hadoop for Predictive Analytics

Apache Hadoop is a free, open-source software platform for writing and running applications that process a large amount of data for predictive analytics. It enables a distributed parallel processing of

### Basics of K-Means and DBSCAN Clustering Models for Predictive Analytics

Unsupervised learning has many challenges for predictive analytics — including not knowing what to expect when you run an algorithm. Each algorithm will produce different results; you’ll never be certain

### How to Visualize the Clusters in a K-Means Unsupervised Learning Model

The Iris dataset is not easy to graph for predictive analytics in its original form. Therefore you have to reduce the number of dimensions by applying a

### Basics of R Programming for Predictive Analytics

R is a programming language originally written for statisticians to do statistical analysis, including predictive analytics. It’s open-source software, used extensively in academia to teach such disciplines

### Basics of Data Types and Structures in R Programming for Predictive Analytics

In R programming for predictive analytics, data types are sometimes confused with data structures. Each variable in the program memory has a data type. Sure, you can get away with having several variables

### How to Call a Function in R Programming for Predictive Analytics

Functions are lines of code that do something useful and concrete. Because these operations are often repeated in a predictive analytics project, they are usually saved with a name so you can

### How to Introduce the Data in R Regression for Predictive Analytics

The dataset you will use in this example is the Auto-MPG dataset, which can be found in the UCI repository. This dataset has 398 observations and 8 attributes plus the label.

### How to Prepare the Data in R Regression for Predictive Analytics

You have to get the data into a form that the algorithm can use to build a predictive analytical model. To do so, you have to take some time to understand the data and to know the structure of the data

### How to Create a Predictive Analytics Model with R Regression

You want to create a predictive analytics model that you can evaluate by using known outcomes. To do that, we’re going to split our dataset into two sets: one for training the model and one for testing

### How to Explain the Predictive Analytical Results of R Regression

Once you create an R regression model for predictive analytics, you want to be able to explain the results of the analysis. To see some useful information about the model, type in the following code:

### How to Outline Testing and Test Data for Predictive Analytics

When your data is ready and you’re about to start building your predictive model for analysis, it’s useful to outline your testing methodology and draft a test plan. Testing should be driven by the business

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