solving Issue 12321 #12324
solving Issue 12321 #12324
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require descriptive names
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| if not match: | ||
| self.weights.append(x.copy()) # Add a new cluster | ||
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| def _similarity(self, w: np.ndarray, x: np.ndarray) -> float: |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: w
Please provide descriptive name for the parameter: x
| """ | ||
| return np.dot(w, x) / (self.num_features) | ||
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| def _learn(self, w: np.ndarray, x: np.ndarray, learning_rate: float = 0.5) -> np.ndarray: |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: w
Please provide descriptive name for the parameter: x
| """ | ||
| return learning_rate * x + (1 - learning_rate) * w | ||
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| def predict(self, x: np.ndarray) -> int: |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: x
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require tests
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| self.num_features = num_features | ||
| self.weights = [] | ||
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| def _similarity(self, weight_vector: np.ndarray, input_vector: np.ndarray) -> float: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function _similarity
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| return np.dot(weight_vector, input_vector) / self.num_features | ||
| def _learn( | ||
| self, w: np.ndarray, x: np.ndarray, learning_rate: float = 0.5 |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: w
Please provide descriptive name for the parameter: x
| """ | ||
| return learning_rate * x + (1 - learning_rate) * w | ||
|
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| def predict(self, x: np.ndarray) -> int: |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: x
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| self.num_features = num_features | ||
| self.weights = [] | ||
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| def _similarity(self, weight_vector: np.ndarray, input_vector: np.ndarray) -> float: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function _similarity
| return np.dot(weight_vector, input_vector) / self.num_features | ||
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| def _learn( | ||
| self, w: np.ndarray, x: np.ndarray, learning_rate: float = 0.5 |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: w
Please provide descriptive name for the parameter: x
| """ | ||
| return learning_rate * x + (1 - learning_rate) * w | ||
|
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| def predict(self, x: np.ndarray) -> int: |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: x
There was a problem hiding this comment.
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@algorithms-keeper reviewto trigger the checks for only added pull request files@algorithms-keeper review-allto trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.
| self.num_features = num_features | ||
| self.weights = [] | ||
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| def _similarity(self, weight_vector: np.ndarray, input_vector: np.ndarray) -> float: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function _similarity
| return np.dot(weight_vector, input_vector) / self.num_features | ||
|
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| def _learn( | ||
| self, w: np.ndarray, x: np.ndarray, learning_rate: float = 0.5 |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: w
Please provide descriptive name for the parameter: x
| """ | ||
| return learning_rate * x + (1 - learning_rate) * w | ||
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| def train(self, data: np.ndarray) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function train
| self.weights[cluster_index], x | ||
| ) | ||
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| def predict(self, x: np.ndarray) -> int: |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: x
There was a problem hiding this comment.
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@algorithms-keeper reviewto trigger the checks for only added pull request files@algorithms-keeper review-allto trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.
| self.num_features = num_features | ||
| self.weights: List[np.ndarray] = [] # Type annotation added here | ||
|
|
||
| def _similarity(self, weight_vector: np.ndarray, input_vector: np.ndarray) -> float: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function _similarity
| return np.dot(weight_vector, input_vector) / self.num_features | ||
|
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||
| def _learn( | ||
| self, w: np.ndarray, x: np.ndarray, learning_rate: float = 0.5 |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: w
Please provide descriptive name for the parameter: x
| """ | ||
| return learning_rate * x + (1 - learning_rate) * w | ||
|
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||
| def train(self, data: np.ndarray) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function train
| self.weights[cluster_index], x | ||
| ) | ||
|
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||
| def predict(self, x: np.ndarray) -> int: |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: x
There was a problem hiding this comment.
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Repository:
Python:
Automated review generated by algorithms-keeper. If there's any problem regarding this review, please open an issue about it.
algorithms-keeper commands and options
algorithms-keeper actions can be triggered by commenting on this PR:
@algorithms-keeper reviewto trigger the checks for only added pull request files@algorithms-keeper review-allto trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.
| self.num_features = num_features | ||
| self.weights: List[np.ndarray] = [] # Correctly typed list of numpy arrays | ||
|
|
||
| def _similarity(self, weight_vector: np.ndarray, input_vector: np.ndarray) -> float: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function _similarity
| return np.dot(weight_vector, input_vector) / self.num_features | ||
|
|
||
| def _learn( | ||
| self, w: np.ndarray, x: np.ndarray, learning_rate: float = 0.5 |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: w
Please provide descriptive name for the parameter: x
| """ | ||
| return learning_rate * x + (1 - learning_rate) * w | ||
|
|
||
| def train(self, data: np.ndarray) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function train
| self.weights[cluster_index], x | ||
| ) | ||
|
|
||
| def predict(self, x: np.ndarray) -> int: |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: x
There was a problem hiding this comment.
Click here to look at the relevant links ⬇️
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Repository:
Python:
Automated review generated by algorithms-keeper. If there's any problem regarding this review, please open an issue about it.
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algorithms-keeper actions can be triggered by commenting on this PR:
@algorithms-keeper reviewto trigger the checks for only added pull request files@algorithms-keeper review-allto trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.
| self.num_features = num_features | ||
| self.weights: List[np.ndarray] = [] # Type annotation added here | ||
|
|
||
| def _similarity(self, weight_vector: np.ndarray, input_vector: np.ndarray) -> float: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function _similarity
| return np.dot(weight_vector, input_vector) / self.num_features | ||
|
|
||
| def _learn( | ||
| self, w: np.ndarray, x: np.ndarray, learning_rate: float = 0.5 |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: w
Please provide descriptive name for the parameter: x
| """ | ||
| return learning_rate * x + (1 - learning_rate) * w | ||
|
|
||
| def train(self, data: np.ndarray) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function train
| self.weights[cluster_index], x | ||
| ) | ||
|
|
||
| def predict(self, x: np.ndarray) -> int: |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: x
There was a problem hiding this comment.
Click here to look at the relevant links ⬇️
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Repository:
Python:
Automated review generated by algorithms-keeper. If there's any problem regarding this review, please open an issue about it.
algorithms-keeper commands and options
algorithms-keeper actions can be triggered by commenting on this PR:
@algorithms-keeper reviewto trigger the checks for only added pull request files@algorithms-keeper review-allto trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.
| self.num_features = num_features | ||
| self.weights: List[np.ndarray] = [] # Type annotation added here | ||
|
|
||
| def _similarity(self, weight_vector: np.ndarray, input_vector: np.ndarray) -> float: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function _similarity
| return np.dot(weight_vector, input_vector) / self.num_features | ||
|
|
||
| def _learn( | ||
| self, w: np.ndarray, x: np.ndarray, learning_rate: float = 0.5) -> np.ndarray: |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: w
Please provide descriptive name for the parameter: x
| """ | ||
| return learning_rate * x + (1 - learning_rate) * w | ||
|
|
||
| def train(self, data: np.ndarray) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function train
| self.weights[cluster_index], x | ||
| ) | ||
|
|
||
| def predict(self, x: np.ndarray) -> int: |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: x
There was a problem hiding this comment.
Click here to look at the relevant links ⬇️
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Repository:
Python:
Automated review generated by algorithms-keeper. If there's any problem regarding this review, please open an issue about it.
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algorithms-keeper actions can be triggered by commenting on this PR:
@algorithms-keeper reviewto trigger the checks for only added pull request files@algorithms-keeper review-allto trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.
| self.num_features = num_features | ||
| self.weights = [] | ||
|
|
||
| def _similarity(self, weight_vector: np.ndarray, input_vector: np.ndarray) -> float: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function _similarity
| return np.dot(weight_vector, input_vector) / self.num_features | ||
|
|
||
| def _learn( | ||
| self, w: np.ndarray, x: np.ndarray, learning_rate: float = 0.5 |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: w
Please provide descriptive name for the parameter: x
| """ | ||
| return learning_rate * x + (1 - learning_rate) * w | ||
|
|
||
| def predict(self, x: np.ndarray) -> int: |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: x
There was a problem hiding this comment.
Click here to look at the relevant links ⬇️
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Repository:
Python:
Automated review generated by algorithms-keeper. If there's any problem regarding this review, please open an issue about it.
algorithms-keeper commands and options
algorithms-keeper actions can be triggered by commenting on this PR:
@algorithms-keeper reviewto trigger the checks for only added pull request files@algorithms-keeper review-allto trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.
| self.num_features = num_features | ||
| self.weights = [] | ||
|
|
||
| def _similarity(self, weight_vector: np.ndarray, input_vector: np.ndarray) -> float: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function _similarity
| return np.dot(weight_vector, input_vector) / self.num_features | ||
|
|
||
| def _learn( | ||
| self, w: np.ndarray, x: np.ndarray, learning_rate: float = 0.5 |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: w
Please provide descriptive name for the parameter: x
| """ | ||
| return learning_rate * x + (1 - learning_rate) * w | ||
|
|
||
| def predict(self, x: np.ndarray) -> int: |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: x
There was a problem hiding this comment.
Click here to look at the relevant links ⬇️
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Repository:
Python:
Automated review generated by algorithms-keeper. If there's any problem regarding this review, please open an issue about it.
algorithms-keeper commands and options
algorithms-keeper actions can be triggered by commenting on this PR:
@algorithms-keeper reviewto trigger the checks for only added pull request files@algorithms-keeper review-allto trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.
| self.num_features = num_features | ||
| self.weights: list[np.ndarray] = [] | ||
|
|
||
| def _similarity(self, weight_vector: np.ndarray, input_vector: np.ndarray) -> float: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function _similarity
| return np.dot(weight_vector, input_vector) / self.num_features | ||
|
|
||
| def _learn( | ||
| self, w: np.ndarray, x: np.ndarray, learning_rate: float = 0.5 |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: w
Please provide descriptive name for the parameter: x
| """ | ||
| return learning_rate * x + (1 - learning_rate) * w | ||
|
|
||
| def predict(self, x: np.ndarray) -> int: |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: x
algorithms-keeper
bot
removed
the
require descriptive names
There was a problem hiding this comment.
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Repository:
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Automated review generated by algorithms-keeper. If there's any problem regarding this review, please open an issue about it.
algorithms-keeper commands and options
algorithms-keeper actions can be triggered by commenting on this PR:
@algorithms-keeper reviewto trigger the checks for only added pull request files@algorithms-keeper review-allto trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.
| self.num_features = num_features | ||
| self.weights: list[np.ndarray] = [] | ||
|
|
||
| def _similarity(self, weight_vector: np.ndarray, input_vector: np.ndarray) -> float: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function _similarity
|
|
||
| return np.dot(weight_vector, input_vector) / self.num_features | ||
|
|
||
| def _learn(self, current_weights: np.ndarray, input_vector: np.ndarray, learning_rate: float = 0.5) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function _learn
| """ | ||
| return learning_rate * input_vector + (1 - learning_rate) * current_weights | ||
|
|
||
| def train(self, input_data: np.ndarray) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function train
| # Update the weights of the assigned cluster | ||
| self.weights[assigned_cluster_index] = self._learn(self.weights[assigned_cluster_index], input_vector) | ||
|
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| def predict(self, input_vector: np.ndarray) -> int: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/adaptive_resonance_theory.py, please provide doctest for the function predict
for more information, see https://pre-commit.ci
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Closing require_tests PRs to prepare for Hacktoberfest |
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