Can
machine learning techniques do better at smaller sample sizes?
Not exact matches
Instead, he said that the new chip, in conjunction with other chips, can be used for very specific kinds of
machine learning techniques, although he didn't elaborate further.
To
do this, data mining uses computational
techniques from statistics,
machine learning and pattern recognition.
«Using the appropriate
machine learning technique enabled us to determine which of these values were the most useful,» Cadamuro said, «and we noticed that in
doing it this way that we picked up a lot we would have missed had we tried to go purely via our intuition.»
In this case, seven different characteristics were necessary for predicting how the materials behaved, and our team's grad student Cory Simon's application of
machine learning techniques greatly sped up the material discovery process by eliminating those that didn't meet the criteria.»
Despite this objective, an investor will always make some emotional and psychological mistakes, but if you can
do things like
learn from your mistakes, use
techniques like checklists, have the right emotional temperament, exhibit a strong work ethic and are a «
learning machine,» he believes some investors can outperform the market.
Yes, I
do think
machine learning / data assimilation
techniques have great potential in the parameterization problem, if they are used within physically informed process models.
Existing
machine -
learning techniques don't work very well on litigation data, he says.
Researchers across academia and industry have applied called
machine learning techniques — a method of computer programming that allows the programme to change when exposed to new data — to train models that can zero in on a person's playstyle, predict what the player will
do in the future, and the kinds of problems that might hinder the player from enjoying the game.