• Study Resource
  • Explore
    • Arts & Humanities
    • Business
    • Engineering & Technology
    • Foreign Language
    • History
    • Math
    • Science
    • Social Science

    Top subcategories

    • Advanced Math
    • Algebra
    • Basic Math
    • Calculus
    • Geometry
    • Linear Algebra
    • Pre-Algebra
    • Pre-Calculus
    • Statistics And Probability
    • Trigonometry
    • other →

    Top subcategories

    • Astronomy
    • Astrophysics
    • Biology
    • Chemistry
    • Earth Science
    • Environmental Science
    • Health Science
    • Physics
    • other →

    Top subcategories

    • Anthropology
    • Law
    • Political Science
    • Psychology
    • Sociology
    • other →

    Top subcategories

    • Accounting
    • Economics
    • Finance
    • Management
    • other →

    Top subcategories

    • Aerospace Engineering
    • Bioengineering
    • Chemical Engineering
    • Civil Engineering
    • Computer Science
    • Electrical Engineering
    • Industrial Engineering
    • Mechanical Engineering
    • Web Design
    • other →

    Top subcategories

    • Architecture
    • Communications
    • English
    • Gender Studies
    • Music
    • Performing Arts
    • Philosophy
    • Religious Studies
    • Writing
    • other →

    Top subcategories

    • Ancient History
    • European History
    • US History
    • World History
    • other →

    Top subcategories

    • Croatian
    • Czech
    • Finnish
    • Greek
    • Hindi
    • Japanese
    • Korean
    • Persian
    • Swedish
    • Turkish
    • other →
 
Profile Documents Logout
Upload
Extreme Data - The Center for Internet Research
Extreme Data - The Center for Internet Research

... In the past, products that only appealed to one in 35,000 people would have never made it to the store shelves, but today the Internet creates marketing channels that make this type of product viable. On Amazon we can find 2 million books, on iTunes, over a million songs. On the Software Superstore, ...
artificial intelligence and life in 2030
artificial intelligence and life in 2030

... parking challenges become obsolete. ...
USI3
USI3

... – Was the concept map laid out in a way that higher order relationships are apparent and easy to follow? Does it have a representative title? ...
CHAPTER 4: LAZY KERNEL-DENSITY
CHAPTER 4: LAZY KERNEL-DENSITY

Real-Time Tweet Analysis with Maltego Carbon 3.5.3.
Real-Time Tweet Analysis with Maltego Carbon 3.5.3.

... Web corpus of 200 billion words as a training corpus) against the Tweets captured by Maltego Carbon / Chlorine in a streaming way • AlchemyAPI, which is part of IBM Watson (recently acquired), retrains its cloudbased (software as a service) algorithm monthly on Web-extracted data (which is mostly un ...
over Lesson 9–5
over Lesson 9–5

DataAnalysis
DataAnalysis

... Click ‘Second Step’ to import data. It’s important to have the both Excel files open.  If an error n°9 occurs, please rename the file and his sheet like this ‘hendastabilityresults.xls’. It’s important to delete file after work instead of having files with same names in your Dowload Folder. ...
Machine Learning Methods for Decision Support
Machine Learning Methods for Decision Support

... learning” implemented as a lookup table). This does not address the problem of how to handle new cases, however. ...
Presentation file I - Discovery Systems Laboratory
Presentation file I - Discovery Systems Laboratory

Status xuPA Knowledge Transfer – 06/08/31
Status xuPA Knowledge Transfer – 06/08/31

... Extracted from the data in a non-intrusive fashion and captured as meta-data Single data representation model can map to multiple storage models Structure and semantics of meta-data help structure queries, search, reports Are embedded tags in the data a possible approach to define ontology structure ...
Clustering Approach to Generalized Pattern Identification Based on Multi-instanced Objects with DARA
Clustering Approach to Generalized Pattern Identification Based on Multi-instanced Objects with DARA

Automated Endoscope Navigation and Advisory System from
Automated Endoscope Navigation and Advisory System from

Artificially Intelligent Virtual Agents
Artificially Intelligent Virtual Agents

... can simply download a zip file containing the infoTabby AIML files (as well as the custom HTML files) on the downloads page of the project.  There are two reasons why this approach will limit you ...
Analyzing the Facebook Friendship Graph
Analyzing the Facebook Friendship Graph

NEURAL NETWORKS
NEURAL NETWORKS

Statistics - Rose
Statistics - Rose

Basic principles of probability theory
Basic principles of probability theory

Sample.pdf
Sample.pdf

Lecture Notes
Lecture Notes

Introduction to Artificial Intelligence
Introduction to Artificial Intelligence

... • This method requires that for each disease the probability it will cause any possible combination of symptoms and the number of possible symptom sets, e, is exponential in the number of basic symptoms. • This huge amount of data is usually not available. ...
Artificial Intelligence
Artificial Intelligence

... algorithm terminates. In case there exist multiple paths leading to the goal, then the path having the smallest distance from the root is preferred. The basic strategy used in this search is only generation of states and their testing for goals but it does not allow filtering of states. (b) Hill Cli ...
INTRODUCTION
INTRODUCTION

... Unsupervised learning is the great promise of the future. Currently, this learning method is limited to networks known as self-organizing maps. These kinds of networks are not in widespread use. They are basically an academic novelty. Yet, they have shown they can provide a solution in a few instanc ...
Preprocessing involves noise removal, skew
Preprocessing involves noise removal, skew

... representative of the characters are extracted. The neighborhood approach for classification identifies the neighbors of the current feature point in the feature space. Shiromone et al. [4] have proposed an encoded character string dictionary for recognition of Tamil characters. This principle of th ...
Well-Tempered Clavier
Well-Tempered Clavier

... • New key-profile values – New problem: Repetitions of notes affect result ...
Rappahannock Trout Restoration Project Meeting at
Rappahannock Trout Restoration Project Meeting at

... The only water quality data are spot measurements of water temperature, pH, discharge, conductivity, and TDS specifically associated with those aquatics samples. In Rappahannock county, some weekly and episodic water quality data is available for the Piney River and quarterly for the NF Thornton (in ...
< 1 ... 141 142 143 144 145 146 147 148 149 ... 193 >

Pattern recognition

Pattern recognition is a branch of machine learning that focuses on the recognition of patterns and regularities in data, although it is in some cases considered to be nearly synonymous with machine learning. Pattern recognition systems are in many cases trained from labeled ""training"" data (supervised learning), but when no labeled data are available other algorithms can be used to discover previously unknown patterns (unsupervised learning).The terms pattern recognition, machine learning, data mining and knowledge discovery in databases (KDD) are hard to separate, as they largely overlap in their scope. Machine learning is the common term for supervised learning methods and originates from artificial intelligence, whereas KDD and data mining have a larger focus on unsupervised methods and stronger connection to business use. Pattern recognition has its origins in engineering, and the term is popular in the context of computer vision: a leading computer vision conference is named Conference on Computer Vision and Pattern Recognition. In pattern recognition, there may be a higher interest to formalize, explain and visualize the pattern, while machine learning traditionally focuses on maximizing the recognition rates. Yet, all of these domains have evolved substantially from their roots in artificial intelligence, engineering and statistics, and they've become increasingly similar by integrating developments and ideas from each other.In machine learning, pattern recognition is the assignment of a label to a given input value. In statistics, discriminant analysis was introduced for this same purpose in 1936. An example of pattern recognition is classification, which attempts to assign each input value to one of a given set of classes (for example, determine whether a given email is ""spam"" or ""non-spam""). However, pattern recognition is a more general problem that encompasses other types of output as well. Other examples are regression, which assigns a real-valued output to each input; sequence labeling, which assigns a class to each member of a sequence of values (for example, part of speech tagging, which assigns a part of speech to each word in an input sentence); and parsing, which assigns a parse tree to an input sentence, describing the syntactic structure of the sentence.Pattern recognition algorithms generally aim to provide a reasonable answer for all possible inputs and to perform ""most likely"" matching of the inputs, taking into account their statistical variation. This is opposed to pattern matching algorithms, which look for exact matches in the input with pre-existing patterns. A common example of a pattern-matching algorithm is regular expression matching, which looks for patterns of a given sort in textual data and is included in the search capabilities of many text editors and word processors. In contrast to pattern recognition, pattern matching is generally not considered a type of machine learning, although pattern-matching algorithms (especially with fairly general, carefully tailored patterns) can sometimes succeed in providing similar-quality output of the sort provided by pattern-recognition algorithms.
  • studyres.com © 2025
  • DMCA
  • Privacy
  • Terms
  • Report