Databases Reference
In-Depth Information
Altogether, this decomposed model makes a profit of $15,000. The
decomposition made it easier for the model to pick up the signals. Note
that with infinite data, all would have been good, and you wouldn't
have needed to decompose. But you work with what you got.
Moreover, you are multiplying errors with this approach, which could
be a problem if you have a reason to believe that those errors are
correlated.
Parting Thoughts
According to Claudia, humans are not meant to understand data. Data
is outside of our sensory systems, and there are very few people who
have a near-sensory connection to numbers. We are instead designed
to understand language.
We are also not meant to understand uncertainty: we have all kinds of
biases that prevent this from happening that are well documented.
Hence, modeling people in the future is intrinsically harder than fig‐
uring out how to label things that have already happened.
Even so, we do our best, and this is through careful data generation,
meticulous consideration of what our problem is, making sure we
model it with data close to how it will be used, making sure we are
optimizing to what we actually desire, and doing our homework to
learn which algorithms fit which tasks.
