Apache Mahout
Apache Mahout
The last edition of this page was on: 2014/10/02
The Completion level of this page is : Low
The last edition of this page was on: 2014/10/02 The Completion level of this page is : Low
SHORT DESCRIPTION
[[has description::According to the home page (oct 1 2014): The Apache Mahout™ project's goal is to build a scalable machine learning library.
Quote: “Currently Mahout supports mainly three use cases: Recommendation mining takes users' behavior and from that tries to find items users might like. Clustering takes e.g. text documents and groups them into groups of topically related documents. Classification learns from exisiting categorized documents what documents of a specific category look like and is able to assign unlabelled documents to the (hopefully) correct category.”]]
TOOL CHARACTERISTICS
Usability
Tool orientation
Data mining type
Manipulation type
IMPORT FORMAT :
EXPORT FORMAT :
| Tool objective(s) in the field of Learning Sciences | |
|
☑ Analysis & Visualisation of data |
☑ Providing feedback for supporting instructors: |
Tool can perform:
- Data extraction of type:
- Transformation of type:
- Data analysis of type:
- Data visualisation of type: (These visualisations can be interactive and updated in "real time")
ABOUT USERS
Tool is suitable for:
Required skills:
STATISTICS: Advanced
PROGRAMMING: Advanced
SYSTEM ADMINISTRATION: Medium
DATA MINING MODELS: Advanced
FREE TEXT
| Tool version : Apache Mahout (blank line) Developed by : | 
|
SHORT DESCRIPTION
According to the home page (oct 1 2014): The Apache Mahout™ project's goal is to build a scalable machine learning library.
Quote: “Currently Mahout supports mainly three use cases: Recommendation mining takes users' behavior and from that tries to find items users might like. Clustering takes e.g. text documents and groups them into groups of topically related documents. Classification learns from exisiting categorized documents what documents of a specific category look like and is able to assign unlabelled documents to the (hopefully) correct category.”
TOOL CHARACTERISTICS
| Tool orientation | Data mining type | Usability |
|---|---|---|
| This tool is designed for general purpose analysis. | This tool is designed for Structured data mining, Text mining. | Authors of this page consider that this tool is difficult to use. |
| Data import format | Data export format |
|---|---|
| . | . |
| Tool objective(s) in the field of Learning Sciences | |
|
☑ Analysis & Visualisation of data |
☑ Providing feedback for supporting instructors: |
Can perform data extraction of type:
Can perform data transformation of type:
Can perform data analysis of type:
Can perform data visualisation of type:
(These visualisations can be interactive and updated in "real time")
ABOUT USER
| Tool is suitable for: | ||||
| Students/Learners/Consumers:☑ | Teachers/Tutors/Managers:☑ | Researchers:☑ | Organisations/Institutions/Firms:☑ | Others:☑ |
| Required skills: | |||
| Statistics: ADVANCED | Programming: ADVANCED | System administration: MEDIUM | Data mining models: ADVANCED |
OTHER TOOL INFORMATION
|
| Mahout-logo-brudman.png |
| Apache Mahout |
| Free&Open source |
| http://mahout.apache.org/ |
| [[has description::According to the home page (oct 1 2014):
The Apache Mahout™ project's goal is to build a scalable machine learning library. Quote: “Currently Mahout supports mainly three use cases: Recommendation mining takes users' behavior and from that tries to find items users might like. Clustering takes e.g. text documents and groups them into groups of topically related documents. Classification learns from exisiting categorized documents what documents of a specific category look like and is able to assign unlabelled documents to the (hopefully) correct category.”]] |
| General analysis |
| Developers/Designers, Researchers |
| Advanced |
| Advanced |
| Medium |
| Advanced |
| Framework/Library/API |
| Structured data mining, Text mining |
| Data analysis |
| difficult to use |
| Low |
Tutorials: