A. Data Mining frame work
The general framework of Knowledge Discovery and Data Mining consists of mainly four stages. The main stages are:
1.Data gathering:
This stage consists of gathering all available information on students. A set of factors that can affect the students’ performance must be identified and collected from the different sources of available data and finally, all the information should be integrated into a dataset.
2.Data Pre-processing:
At this stage the dataset is prepared to apply the data mining techniques. Traditional pre-processing methods such as data cleaning, transformation of variables, and data partitioning have to be applied.
3. Data mining:
Different data mining algorithms are applied to the dataset. The
…show more content…
In [1] white box classification techniques are used to predict the dropouts. Decision trees and rules induction algorithms and evolutionary algorithms are mainly used as the “white box” classification techniques. White box classification algorithms obtain models that can explain their predictions at a higher level of abstraction by IF-THEN rules. A decision tree is a set of conditions organized in a hierarchical structure. An instance can be classified by following the path of satisfied conditions from the root of the tree until a leaf is reached, which corresponds to a class label. Rule induction algorithms usually employ a specific-to-general approach, in which obtained rules are generalized until a satisfactory description of each class is …show more content…
Genetic Programming (GP) is a machine learning technique used to optimize a population of computer programs according to a fitness function determined by a program’s ability to perform a given computational task. Genetic programming has been applied with success in various complex optimization, search and classification problems. Interpretable Classification Rule Mining algorithm (ICRM) that employs Grammar based Genetic Programming (G3P) to evolve rule-based classifiers and has been shown to perform well in other classification domains. G3P is a variant of genetic programming in which a grammar is defined and the evolutionary process proceeds, making sure that every individual generated is legal with respect to the grammar. The algorithm iterates to find the best rules for the different classes. A context-free grammar is used to specify which relational operators are allowed to appear in the antecedents of the rules and which attribute must appear in the consequents or the class. The use of a grammar provides expressiveness, flexibility, and ability to restrict the search space in the search for rules. The implementation of constraints using a grammar is a very natural way to express the syntax of rules. The rules must be constructed
\subsection{Creation of Matching Entries ({\it MakeMatchingEntries'})} \label{sec:make-matching} \label{sec:match} Procedure ${\it MakeMatchingEntries'}$ takes a decoding entry set and a pattern as input and outputs a newly created set that contains the entries that match the input pattern. Note that not every entry in the newly created set is the same entry in the input entries because the exclusion conditions were modified. The exclusion conditions that are invalidated by the input pattern are removed from the exclusion condition set of output entries. In addition, when all the matching patterns are invalidated, the unmatching patterns are expanded to their opcode patterns. Procedure ${\it MakeMatchingEntries'}$ consists of the following
Unit 9, Lesson 9: Digital Business Cards and Brochures 54.12— Define data mining. 54.13— Identify basic tools and techniques of data mining. 54.14— Explain the use of data mining in Customer Relationship Management (CRM). 54.15—Identify ethical issues of data mining. Lesson Intro Reading 9.9: Activity 9.9: ____________________________________________________________________________ Unit 9, Lesson 10: Digital Business Cards and Brochures 55.01—Publicize e-commerce site through non-Internet means such as mail, press release, broadcast media, print media, and specialty advertising.
The dataset used in the analysis is the grades.dat; it was used to analyze the performance of the students in the GPA and the final. The dataset includes information collected from the survey of 105 students and includes variables such as performance and demographic variables. The variable GPA measures the performance
Step 2. Develop Positive and Negative Examples This is the key step, because the positive examples must contain all the essential attributes, yet they may contain some nonessential attributes that are gradually eliminated. Negative examples may have some of, but not all, the essential
The healthcare industry generates a great amount of data every day, as a form of record keeping, patient care, compliance, and regulatory requirements. Just a decade ago, all this data was stored in the form of hard copy form, now it is rapidly transforming to digital data which is called EMR (Electronic Medical Record). The digitalization of the healthcare has not just reduced cost of care, but also improved quality of care due to the abundance data that organizations receive from the EMR to identify the flaws in their system. I work in the healthcare industry where improving quality of care is our primary goal. We use software called eCW , which is an integrated system.
C. Further languages should be integerable without modifying the source code. D. The architecture should allow the integration of new modules, e.g. for additional implicit expressions. E. When needed, adding and modifying rules should be simple. HeidelTime is developed as a rule based system.
1. What are some important steps in interpreting data from high stakes assessments? In order to make assessment data useful teachers must understand what information is being reported and determine if additional information is necessary to understand student performance. Specifically, for assessment results for students with disabilities, teachers would have to identify what accommodations were being used.
EFV GMA Task 1: A1. Describe the target behavior: When given a non-preferred task, specifically a difficult independent work involving reading comprehension or math problem solving by his 4th grade general education teacher in Dexter’s classroom, Dexter 9 out 10 times flaps his hands speaks loudly and refuses to do the task until he is removed from class. Thereby avoiding all steps of completing the work. A2. Determine the antecedents/triggers for the target behavior: Prior to the target behavior, his 4th grade teacher in the classroom assigns a task to complete on his own that is challenging for Dexter involving reading comprehension or math problem solving.
Computers permit large amounts of data to be stored, either on the computer's hard disk or in portable diskettes. Data Manipulation and Processing Data manipulation and processing are performed to obtain useful information from data previously entered into the system. Data manipulation embraces two types of operations: operations needed to remove errors and update current data sets and operations using analytical techniques to answer specific questions formulated by the user. The manipulation process can range from the simple overlay of two or more maps to a complex extraction of disparate pieces of information from a wide variety of sources. Data Output Data output refers to the display or presentation of data employing commonly used output formats that include maps, graphs, reports, tables, and charts, either as a hard-copy, as an image on the screen, or as a text file that can be carried into other software programs for further analysis.
Syntactic rules: They play the role of foundation like how the sentence should be structured. For example, it could grammar, or vowel use in a sentence. Semantic rules: This is the most important rule of language to govern because it gives the word a specific meaning. This way words can be used by most people. Yet, when these rules are used well like people misuse the word or overuse it.
The study is anchored on the theory of educational productivity by Herbert J. Walberg. Walberg’s theory tackles about the influences on learning that affects the academic performance of a student. It is an exploration of academic achievement wherein Walberg used a variety of methods on how to identify the factors that affects the academic performance of a student. He analyzed his theory with the help of different theorists and integrated his study with over 3000 studies. In his theory, he classified 11 influential domains of variables, 8 of them were affected by social-emotional influences namely, classroom management, parental support, student-teacher interactions, social-behavioral attributes, motivational-effective attributes, the peer