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SAS Visual Data Mining and Machine Learning Features

What are the features of SAS Visual Data Mining and Machine Learning?

Data Analysis

  • Analysis
  • Data Interaction

Decision Making

  • Modeling
  • Data Visualizations
  • Report Generation

Top Rated SAS Visual Data Mining and Machine Learning Alternatives

Filter for Features

Statistical Tool

Scripting

Supports a variety of scripting environments

Not enough data

Data Mining

Mines data from databases and prepares data for analysis

Not enough data

Algorithms

Applies statistical algorithms to selected data

Not enough data

Data Analysis

Analysis

Analyzes both structured and unstructured data 10 reviewers of SAS Visual Data Mining and Machine Learning have provided feedback on this feature.
85%
(Based on 10 reviews)

Data Interaction

Based on 10 SAS Visual Data Mining and Machine Learning reviews. Interacts with data to prepare it for visualizations and models
90%
(Based on 10 reviews)

Decision Making

Modeling

Offers modeling capabilities 11 reviewers of SAS Visual Data Mining and Machine Learning have provided feedback on this feature.
86%
(Based on 11 reviews)

Data Visualizations

Based on 11 SAS Visual Data Mining and Machine Learning reviews. Creates data visualizations or graphs
91%
(Based on 11 reviews)

Report Generation

As reported in 11 SAS Visual Data Mining and Machine Learning reviews. Generates reports of data performance
91%
(Based on 11 reviews)

Data Unification

Unifies information on a singular platform

Not enough data

Model Development

Language Support

Supports programming languages such as Java, C, or Python. Supports front-end languages such as HTML, CSS, and JavaScript

Not enough data

Drag and Drop

Offers the ability for developers to drag and drop pieces of code or algorithms when building models

Not enough data

Pre-Built Algorithms

Provides users with pre-built algorithms for simpler model development

Not enough data

Model Training

Supplies large data sets for training individual models

Not enough data

Pre-Built Algorithms

Provides users with pre-built algorithms for simpler model development

Not enough data

Model Training

Supplies large data sets for training individual models

Not enough data

Feature Engineering

Transforms raw data into features that better represent the underlying problem to the predictive models

Not enough data

Machine/Deep Learning Services

Computer Vision

Offers image recognition services

Not enough data

Natural Language Processing

Offers natural language processing services

Not enough data

Natural Language Generation

Offers natural language generation services

Not enough data

Artificial Neural Networks

Offers artificial neural networks for users

Not enough data

Computer Vision

Offers image recognition services

Not enough data

Natural Language Understanding

Offers natural language understanding services

Not enough data

Natural Language Generation

Offers natural language generation services

Not enough data

Deep Learning

Provides deep learning capabilities

Not enough data

Deployment

Managed Service

Manages the intelligent application for the user, reducing the need of infrastructure

Not enough data

Application

Allows users to insert machine learning into operating applications

Not enough data

Scalability

Provides easily scaled machine learning applications and infrastructure

Not enough data

Managed Service

Manages the intelligent application for the user, reducing the need of infrastructure

Not enough data

Application

Allows users to insert machine learning into operating applications

Not enough data

Scalability

Provides easily scaled machine learning applications and infrastructure

Not enough data

System

Data Ingestion & Wrangling

Gives user ability to import a variety of data sources for immediate use

Not enough data

Language Support

Supports programming languages such as Java, C, or Python. Supports front-end languages such as HTML, CSS, and JavaScript

Not enough data

Drag and Drop

Offers the ability for developers to drag and drop pieces of code or algorithms when building models

Not enough data