Amazon ML (Amazon Machine Learning) is offered by Amazon as a general purpose supervised classification service. They don't even bother to mention what algorithms are being used, they just use the generic term "ML models".
From their Key Concepts page:
An ML model is a mathematical model that generates predictions by finding patterns in your data. Amazon ML supports three types of ML models: binary classification, multiclass classification and regression.
Upon digging deeper, they state in their FAQ:
Amazon Machine Learning currently uses an industry-standard logistic regression algorithm to generate models.
Based on this, one would assume that logistic regression can pull off anything that an SVM, an RF or a Neural Net can. Is that the case?
Isn't logistic regression limited to linearly separable models? Isn't it just a special case of Neural Net (i.e. one layer perceptron) ?
And is it really an "industry standard", and is it really so versatile that Amazon would favor it over something more complex ?