multiple regression functions with table argument #1763
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given a table, the input cols, and the output col. - multiple-regression-coeffs: returns list of coefficients - multiple-regression-table: returns coeffs as 2-col table - multiple-regression-fun: returns predictor function
src/arr/trove/statistics.arr
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| fun multiple-regression-coeffs(t :: Table, input-cols :: List<String>, output-col :: String): | ||
| doc: "returns a list of regression coefficients, given a table, a list of independent columns, and the corresponding output column" | ||
| # spy: t, input-cols, output-col end | ||
| x_s_s = zip-num-lists(input-cols.map(lam(col-name :: String): t.get-column(col-name) end)) |
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This might be better done as x_s_s = table-to-matrix(t.select-columns(input-cols)) using https://github.com/brownplt/pyret-lang/blob/horizon/src/arr/trove/matrices.arr#L1047 and https://github.com/brownplt/pyret-lang/blob/horizon/src/js/trove/table.js#L712
src/arr/trove/statistics.arr
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| # spy: intercepts end | ||
| mx_X = intercepts.augment(MX.lists-to-matrix(x_s_s)) | ||
| # spy: mx_X end | ||
| mx_Y = MX.col-matrix.make(raw-array-from-list(y_s)) |
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This could also be done as table-to-matrix(t.get-columns([list: output-col]), for symmetry's sake; it's not any more or less efficient, per se.
src/arr/trove/statistics.arr
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| MX.mtx-to-list(MX.mtx-least-squares-solve(mx_X, mx_Y)) | ||
| end | ||
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| fun multiple-regression-table(t :: Table, input-cols :: List<String>, output-col :: String): |
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General comment: Didn't @schanzer implement these functions in his starter files somewhere? (I'm pretty certain I gave him nearly this code, so it's worth double-checking...)
| [table-from-columns: {"coefficient-name"; coeff-names}, {"coefficient-value"; B}] | ||
| end | ||
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| fun multiple-regression-fun(t :: Table, input-cols :: List<String>, output-col :: String) -> (List<Number> -> Number): |
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This function can't possibly be needed as written; don't we have multiple-regression already? This looks like copy-pasted code, and fiddly code at that, so we should deduplicate it.
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The difference is that the current trio of functions take a table, and column names as arguments. The Bootstrap group decided that all three outputs (viz., list of coefficients, table of coefficients, and predictor function) were needed, and it wasn't clear which one (or perhaps two) should be treated as basic.
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That's not my point. We already have https://github.com/brownplt/pyret-lang/blob/horizon/src/arr/trove/statistics.arr#L236-L244 that defines B_pred_fun; don't duplicate that code.
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It's not a duplicate. multiple-regression-fun calls multiple-regression-coeffs to get a list of coefficients, which it calls B. The B_pred_fn then uses fold2 to do a dot-product its argument list with B. It avoids having to convert the argument list to a vector.
In the original multiple-regression, we get a vector of coefficients, which it calls B. Its B_pred_fn converts its argument list into a vector and then performs a vector dot product with the vector B.
The only commonality between the two B_pred_fns is that they check the length of their incoming list the same way to decide if an exception needs to be thrown. Once past that check, the body is different.
One could write an external function that is called in both places (with B as argument) to create B_pred_fn, but even so, one would have to do an extra list/vector casting in one of the two functions, so that the Bs are the same type.
statistics.arr: Added three functions that perform multiple regression given a table, the input cols, and the output col.