Please enable JavaScript.
Coggle requires JavaScript to display documents.
Azure-Machine-Learning-Service (Extract Information for Text (Text…
-
-
-
-
-
-
-
Performs cleaning operation, like removal of stop-words, case-normalization
Converts words to values for use in NLP tasks, like recommender, named entity recognition, machine translation
-
Makes forecasts by estimating the like yes or no, true or false relationship between values
Answers questions like: How much or how many?
-
-
-
-
-
-
-
-
-
Fast training, linear model
Linear model, small data sets
Accurate, fast training times
Accurate, long training times
Accurate, fast training times, large memory footprint
-
-
-
Collaborative filtering, better performance with lower cost by reducing dimensionality
-
-
-
-
-
Under 100 features, aggressive boundary
-
High accuracy, better efficiency
-
-
-
-
-
-
-
Fast training times, linear model
Accuracy, long training times
Accuracy, fast training times
-
Non-parametric, fast training times and scalable
Answers complex questions with
multiple possible answers
Answers questions like: Is this A or B or C or D?
-
-
-
-
-
-
Under 100 features, linear model
Fast training, linear model
High accuracy, better efficiency
Fast training, linear model
Accurate, fast training, large memory footprint
Accurate, long training times
Answers simple two-choice questions,
Makes forecasts by estimating the like yes or no, true or false
Answers questions like: Is this A or B?
-
-
