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Fixes: 6216 | Support vector machines #6237

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Bjiornulf
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Describe your change:

  • Add an algorithm?
  • Fix a bug or typo in an existing algorithm?
  • Documentation change?

Checklist:

  • I have read CONTRIBUTING.md.
  • This pull request is all my own work -- I have not plagiarized.
  • I know that pull requests will not be merged if they fail the automated tests.
  • This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
  • All new Python files are placed inside an existing directory.
  • All filenames are in all lowercase characters with no spaces or dashes.
  • All functions and variable names follow Python naming conventions.
  • All function parameters and return values are annotated with Python type hints.
  • All functions have doctests that pass the automated testing.
  • All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
  • If this pull request resolves one or more open issues then the commit message contains Fixes: #{$ISSUE_NO}.

@ghost ghost added the require descriptive names This PR needs descriptive function and/or variable names label Jul 6, 2022
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Click here to look at the relevant links ⬇️

🔗 Relevant Links

Repository:

Python:

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"""

def __init__(
self, *, C: float = np.inf, kern: str = "linear", gamma: float = None
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Please provide descriptive name for the parameter: C

raise ValueError(f"Unknown kernel: {kern}")

# kernels
def __linear(self, x: ndarray, y: ndarray) -> float:
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Please provide descriptive name for the parameter: x

Please provide descriptive name for the parameter: y

def __linear(self, x: ndarray, y: ndarray) -> float:
return np.dot(x, y)

def __rbf(self, x: ndarray, y: ndarray) -> float:
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Please provide descriptive name for the parameter: x

Please provide descriptive name for the parameter: y

def __rbf(self, x: ndarray, y: ndarray) -> float:
return np.exp(-(self.gamma * np.dot(x - y, x - y)))

def fit(self, xs: list[ndarray], y: ndarray) -> None:
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Please provide descriptive name for the parameter: y

(n,) = np.shape(y)

# l = v because flake8...
def to_minimize(v: ndarray) -> float:
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Please provide descriptive name for the parameter: v

b += y[i] - y[i] * l_star[i] * self.kern(xs[i], xs[j])
self.b = b / n

def predict(self, x: ndarray) -> int:
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Please provide descriptive name for the parameter: x

@ghost ghost added the awaiting reviews This PR is ready to be reviewed label Jul 6, 2022
@Bjiornulf
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could you please help me resolve these naming issues correctly? For example C was picked to match sklearns syntax. For the kernels, I would like to NOT have overly descriptive names, since the arguments are just vectors (ndarray).

@cclauss cclauss closed this Jul 7, 2022
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2 participants