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Your average data-set does not fit into 3 nice categories like the Iris data-set does. For example, with the Iris data set if you know the sepal length and the
by rampage101 10y ago
Your average data-set does not fit into 3 nice categories like the Iris data-set does. For example, with the Iris data set if you know the sepal length and the petal length, you can say with near certainty which type of flower it is. Even trying to classify other objects in nature is much harder than this dataset.
Now let's take sentiment analysis which tries to determine if some words are positive or negative. If someone said: 'that new machine learning algorithm is so sick'. The algorithm has no way of knowing that sick may be slang to mean good, because the system looks up 'sick' and finds that is a negative word. Sentiment analysis has no way of defining sarcasm or other natural language terms.
- bogomipz 10y agoThanks for the explanation and why the Iris data set is so ubiquitous in ML tutorials.
- morgante 10y ago> Sentiment analysis has no way of defining sarcasm or other natural language terms. Of course it can. If humans are capable of detecting a given inflection, computers absolutely can as well (given enough data). Any sentiment analysis algorithm which classifies "that new machine learning algorithm is so sick" as negative is not worth an ounce of consideration. Compared to other problems, that is absolutely trivial to classify, especially since you're typically training off data sets which already include such vernacular.