Datumbox Machine Learning Framework currently offers 14 different functions as part of the Machine Learning platform and all the functions use several sophisticated classification techniques and they are accessible via our REST API.
Predictive Analytics API
Twitter Sentiment Analysis
Adult Content Detection
Contact for Pricing
Small (<50 employees), Medium (50 to 1000 employees), Enterprise (>1001 employees)
Datumbox offers a Machine Learning platform composed of 14 classifiers and Natural Language processing functions. Functions include sentiment analysis, topic classification, readability assessment, language detection, and much more. The Datumbox API provides developer access using REST-like RPC-style operations over HTTP POST requests. The API accesses all of the platform functions. Responses are JSON formatted. Access requires a user account and API Key. Datumbox API is a web service which allow to use tools from the website, software or mobile application. The API gives access to all of the supported functions of Datumbox service. Datumbox Web Service uses “REST-Like” RPC-style operations over HTTP POST requests with parameters URL encoded into the request and its response is encoded in JSON. It is designed to be easy to use and one can implement it in any model computer language that allows to generat web requests. At the moment Datumbox API currently allows to build applications that make use of Text Analysis and Natural Language Processing techniques such as Online Marketing Tools, SEO Tools, Social Media Monitoring services, Anti-Spam filters and other Text Classification apps. The currently supported API functions are: Sentiment Analysis, Twitter Sentiment Analysis, Subjectivity Analysis, Topic Classification, Spam Detection, Adult Content Detection, Readability Assessment, Language Detection, Commercial Detection, Educational Detection, Gender Detection, Keyword Extraction, Text Extraction and Document Similarity.
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More Information on Predictive Analysis Process
For more information of predictive analytics process, please review the overview of each components in the predictive analytics process: data collection (data mining), data analysis, statistical analysis, predictive modeling and predictive model deployment.