machine learning mini projects


The advantage of a machine learning approach is that it is more adaptable, robust, flexible, and maintainable. Our goal is to design a feature vector representation such that it provides useful information to a learning algorithm to automatically build five classifiers, one for each question type.

A Machine Learning Approach for Tracking and Predicting Student Performance in Degree Programs
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Accurately predicting students future performance based on their ongoing academic records is crucial for effectively carrying out necessary pedagogical interventions to ensure students on-time and satisfactory graduation. Although there is a rich literature on predicting student performance when solving problems or studying for courses using data-driven approaches, predicting student performance in completing degrees (eg, college programs) is much less studied and faces new challenges:(1) Students differ tremendously in terms of backgrounds

Detecting spam blogs: A machine learning approach
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Weblogs or blogs are an important new way to publish information, engage in discussions, and form communities on the Internet. The Blogosphere has unfortunately been infected by several varieties of spam-like content. Blog search engines, for example, are inundated by

A machine – learning approach to automated knowledge-base building for remote sensing image analysis with GIS data
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A machine learning approach to automated building of knowledge bases for image analysis expert systems incorporating GIS data is presented. The method uses an inductive learning algorithm to generate production rules from training data. With this method, building a

A machine learning approach for automatic student model discovery.
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Student modeling is one of the key factors that affects automated tutoring systems in making instructional decisions. A student model is a model to predict the probability of a student making errors on given problems. A good student model that matches with student behavior

A machine learning approach to pronoun resolution in spoken dialogue
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We apply a decision tree based approach to pronoun resolution in spoken dialogue. Our system deals with pronouns with NP-and non-NP-antecedents. We present a set of features designed for pronoun resolution in spoken dialogue and determine the most promising

A machine learning approach to anomaly detection
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Much of the intrusion detection research focuses on signature (misuse) detection, where models are built to recognize known attacks. However, signature detection, by its nature, cannot detect novel attacks. Anomaly detection focuses on modeling the normal behavior

Automatic vandalism detection in Wikipedia: Towards a machine learning approach
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Since the end of 2006 several autonomous bots are, or have been, running on Wikipedia to keep the encyclopedia free from vandalism and other damaging edits. These expert systems, however, are far from optimal and should be improved to relieve the human editors

Classification of musical genre: a machine learning approach .
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In this paper, we investigate the impact of machine learning algorithms in the development of automatic music classification models aiming to capture genres distinctions. The study of genres as bodies of musical items aggregated according to subjective and local criteria

Identification and resolution of Chinese zero pronouns: A machine learning approach
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In this paper, we present a machine learning approach to the identification and resolution of Chinese anaphoric zero pronouns. We perform both identification and resolution automatically, with two sets of easily computable features. Experimental results show that

A machine learning approach for filtering Monte Carlo noise.
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The most successful approaches for filtering Monte Carlo noise use feature-based filters (eg, cross-bilateral and cross non-local means filters) that exploit additional scene features such as world positions and shading normals. However, their main challenge is finding the

Identifying non-referential it: a machine learning approach incorporating linguistically motivated patterns
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In this paper, we present a machine learning system for identifying non-referential it. Types of non-referential it are examined to determine relevant linguistic patterns. The patterns are incorporated as features in a machine learning system which performs a binary classification

A machine learning approach to conjoint analysis
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Choice-based conjoint analysis builds models of consumer preferences over products with answers gathered in questionnaires. Our main goal is to bring tools from the machine learning community to solve this problem more efficiently. Thus, we propose two algorithms

A machine learning approach to foreign key discovery.
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We study the problem of automatically discovering semantic associations between schema elements, namely foreign keys. This problem is important in all applications where data sets need to be integrated that are structured in tables but without explicit foreign key constraints

Inducing deterministic Prolog parsers from treebanks: A machine learning approach
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This paper presents a method for constructing deterministic Prolog parsers from corpora of parsed sentences. Our approach uses recent machine learning methods for inducing Prolog rules from examples (inductive logic programming). We discuss several advantages of this

A machine learning approach to automatic term extraction using a rich feature set
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In this paper we propose an automatic term extraction approach that uses machine learning incorporating varied and rich features of candidate terms. In our preliminary experiments, we also tested different attribute selection methods to verify which features are more relevant for

Automated census record linking: A machine learning approach
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Thanks to the availability of new historical census sources and advances in record linking technology, economic historians are becoming big data genealogists. Linking individuals over time and between databases has opened up new avenues for research into

A machine learning approach for MRI brain tumor classification
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A new method for the denoising, extraction and tumor detection on MRI images is presented in this paper. MRI images help physicians study and diagnose diseases or tumors present in the brain. This work is focused towards helping the radiologist and physician to have a

Rule based systems for big data: a machine learning approach
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The series Studies in Big Data (SBD) publishes new developments and advances in the various areas of Big Data- quickly and with a high quality. The intent is to cover the theory, research, development, and applications of Big Data, as embedded in the fields of engineering, computer

A machine learning approach to recipe text processing
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We propose a machine learning approach to recipe text processing problem aiming at converting a recipe text to a work flow. In this paper, we focus on the natural language processing (NLP) such as word identification, named entity recognition, and syntactic

Supporting the Requirements Prioritization Process. A Machine Learning approach .
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Requirements prioritization plays a key role in the requirements engineering process, in particular with respect to critical tasks such as requirements negotiation and software release planning. This paper presents a novel framework which is based on a requirements

Revising Rules to Capture Requirements Traceability Relations: A Machine Learning Approach .
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In this paper we present a machine learning approach for generating requirements traceability relations. This approach is based on a new learning algorithm that produces traceability rules which are able to capture traceability relations between requirement

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