From 422e383d8f825cfb9d58e89b97d0348c480ba31a Mon Sep 17 00:00:00 2001 From: samhithamuvva <163280630+samhithamuvva@users.noreply.github.com> Date: Thu, 10 Oct 2024 12:43:06 -0700 Subject: [PATCH] Add logistic regression sentiment analysis --- README.md | 21 +- .../logreg/examples/evaluate_textcat.py | 138 ++++++ .../logreg/myenv/Scripts/Activate.ps1 | 443 ++++++++++++++++++ spacy/pipeline/logreg/myenv/Scripts/activate | 69 +++ spacy/pipeline/logreg/myenv/Scripts/f2py.exe | Bin 0 -> 108421 bytes .../logreg/myenv/Scripts/markdown-it.exe | Bin 0 -> 106377 bytes .../logreg/myenv/Scripts/numpy-config.exe | Bin 0 -> 108421 bytes spacy/pipeline/logreg/myenv/Scripts/pip.exe | Bin 0 -> 108426 bytes .../pipeline/logreg/myenv/Scripts/pip3.10.exe | Bin 0 -> 108426 bytes spacy/pipeline/logreg/myenv/Scripts/pip3.exe | Bin 0 -> 108426 bytes .../logreg/myenv/Scripts/pygmentize.exe | Bin 0 -> 106372 bytes .../pipeline/logreg/myenv/Scripts/python.exe | Bin 0 -> 264176 bytes .../pipeline/logreg/myenv/Scripts/pythonw.exe | Bin 0 -> 252912 bytes spacy/pipeline/logreg/myenv/Scripts/spacy.exe | Bin 0 -> 106375 bytes spacy/pipeline/logreg/myenv/Scripts/tqdm.exe | Bin 0 -> 106364 bytes spacy/pipeline/logreg/myenv/Scripts/typer.exe | Bin 0 -> 106365 bytes .../pipeline/logreg/myenv/Scripts/weasel.exe | Bin 0 -> 106364 bytes spacy/pipeline/logreg/myenv/pyvenv.cfg | 3 + spacy/pipeline/logreg/src/pure_Logistic.py | 224 +++++++++ .../logreg/tests/test_pure_logistic.py | 225 +++++++++ .../test_textcat/test_pure_logistic.py | 72 --- spacy/pipeline/textcat/pure_Logistic.py | 170 ------- .../textcat/pure_logistic_textcat.ipynb | 129 ----- 23 files changed, 1116 insertions(+), 378 deletions(-) create mode 100644 spacy/pipeline/logreg/examples/evaluate_textcat.py create mode 100644 spacy/pipeline/logreg/myenv/Scripts/Activate.ps1 create mode 100644 spacy/pipeline/logreg/myenv/Scripts/activate create mode 100644 spacy/pipeline/logreg/myenv/Scripts/f2py.exe create mode 100644 spacy/pipeline/logreg/myenv/Scripts/markdown-it.exe create mode 100644 spacy/pipeline/logreg/myenv/Scripts/numpy-config.exe create mode 100644 spacy/pipeline/logreg/myenv/Scripts/pip.exe create mode 100644 spacy/pipeline/logreg/myenv/Scripts/pip3.10.exe create mode 100644 spacy/pipeline/logreg/myenv/Scripts/pip3.exe create mode 100644 spacy/pipeline/logreg/myenv/Scripts/pygmentize.exe create mode 100644 spacy/pipeline/logreg/myenv/Scripts/python.exe create mode 100644 spacy/pipeline/logreg/myenv/Scripts/pythonw.exe create mode 100644 spacy/pipeline/logreg/myenv/Scripts/spacy.exe create mode 100644 spacy/pipeline/logreg/myenv/Scripts/tqdm.exe create mode 100644 spacy/pipeline/logreg/myenv/Scripts/typer.exe create mode 100644 spacy/pipeline/logreg/myenv/Scripts/weasel.exe create mode 100644 spacy/pipeline/logreg/myenv/pyvenv.cfg create mode 100644 spacy/pipeline/logreg/src/pure_Logistic.py create mode 100644 spacy/pipeline/logreg/tests/test_pure_logistic.py delete mode 100644 spacy/pipeline/test_textcat/test_pure_logistic.py delete mode 100644 spacy/pipeline/textcat/pure_Logistic.py delete mode 100644 spacy/pipeline/textcat/pure_logistic_textcat.ipynb diff --git a/README.md b/README.md index c3e56ca2f..2ef905ff5 100644 --- a/README.md +++ b/README.md @@ -227,6 +227,9 @@ nlp = en_core_web_sm.load() doc = nlp("This is a sentence.") ``` +📖 **For more info and examples, check out the +[models documentation](https://spacy.io/docs/usage/models).** + ## 📊 Custom Sentiment Analysis with Logistic Regression (spaCy-based) This repository also includes a custom **Logistic Regression** sentiment analysis model built using spaCy, without using scikit-learn. The model classifies text as positive or negative based on a dataset such as IMDb reviews. @@ -234,24 +237,28 @@ This repository also includes a custom **Logistic Regression** sentiment analysi To run the logistic regression model: ```bash python pure_Logistic.py -```This script processes the dataset using spaCy, trains the logistic regression model, and outputs the results. - +``` +This script processes the dataset using spaCy, trains the logistic regression model, and outputs the results. ### Testing and Evaluation +To run tests and evaluate the model's performance: To run tests and evaluate the model's performance, use: + ```bash python test_pure_logistic.py ``` - -In your test script, import the PureLogisticTextCategorizer class for evaluation: +To use the model in your own code: +In your test script, ```bash +import the PureLogisticTextCategorizer class for evaluation: from pure_Logistic import PureLogisticTextCategorizer ``` + +# Initialize and use the classifier +categorizer = PureLogisticTextCategorizer() +``` This enables you to evaluate the logistic regression classifier on your test cases. -📖 **For more info and examples, check out the -[models documentation](https://spacy.io/docs/usage/models).** - ## ⚒ Compile from source The other way to install spaCy is to clone its diff --git a/spacy/pipeline/logreg/examples/evaluate_textcat.py b/spacy/pipeline/logreg/examples/evaluate_textcat.py new file mode 100644 index 000000000..5de2ef84e --- /dev/null +++ b/spacy/pipeline/logreg/examples/evaluate_textcat.py @@ -0,0 +1,138 @@ +import spacy +from spacy.training import Example +from spacy.tokens import Doc +from typing import Dict, List + +# Import the custom logistic classifier +from pure_Logistic import make_pure_logistic_textcat + + +# Registering the custom extension 'textcat' to store predictions +if not Doc.has_extension("textcat"): + Doc.set_extension("textcat", default={}) + + +# Sample training and testing data +TRAIN_DATA = [ + ("This product is amazing! I love it.", {"cats": {"positive": 1.0, "negative": 0.0}}), + ("The service was excellent and staff very friendly.", {"cats": {"positive": 1.0, "negative": 0.0}}), + ("I'm really impressed with the quality.", {"cats": {"positive": 1.0, "negative": 0.0}}), + ("Best purchase I've made in years!", {"cats": {"positive": 1.0, "negative": 0.0}}), + ("The features work exactly as advertised.", {"cats": {"positive": 1.0, "negative": 0.0}}), + ("This is terrible, complete waste of money.", {"cats": {"positive": 0.0, "negative": 1.0}}), + ("Poor customer service, very disappointing.", {"cats": {"positive": 0.0, "negative": 1.0}}), + ("The product broke after one week.", {"cats": {"positive": 0.0, "negative": 1.0}}), + ("Would not recommend to anyone.", {"cats": {"positive": 0.0, "negative": 1.0}}), + ("Save your money and avoid this.", {"cats": {"positive": 0.0, "negative": 1.0}}) +] + +TEST_DATA = [ + ("Great product, highly recommend!", {"cats": {"positive": 1.0, "negative": 0.0}}), + ("Not worth the price at all.", {"cats": {"positive": 0.0, "negative": 1.0}}), + ("Everything works perfectly.", {"cats": {"positive": 1.0, "negative": 0.0}}), + ("Disappointed with the results.", {"cats": {"positive": 0.0, "negative": 1.0}}) +] + +def calculate_metrics(true_positives: int, true_negatives: int, false_positives: int, false_negatives: int) -> Dict[str, float]: + """Calculate evaluation metrics based on counts.""" + total = true_positives + true_negatives + false_positives + false_negatives + accuracy = (true_positives + true_negatives) / total if total > 0 else 0 + precision = true_positives / (true_positives + false_positives) if (true_positives + false_positives) > 0 else 0 + recall = true_positives / (true_positives + false_negatives) if (true_positives + false_negatives) > 0 else 0 + f1 = 2 * (precision * recall) / (precision + recall) if (precision + recall) > 0 else 0 + + return { + "accuracy": accuracy, + "precision": precision, + "recall": recall, + "f1": f1 + } + +def evaluate_model(nlp, test_data): + """Evaluate the model using the test data.""" + true_positives = true_negatives = false_positives = false_negatives = 0 + predictions = [] + + for text, annotations in test_data: + doc = nlp(text) + true_cats = annotations["cats"] + pred_cats = doc._.textcat # Predictions from the custom model + + # Extract scores for 'positive' and 'negative' + pred_positive_score = pred_cats["positive"] if "positive" in pred_cats else 0.0 + true_positive_score = true_cats.get("positive", 0.0) + + pred_positive = float(pred_positive_score) > 0.5 + true_positive = float(true_positive_score) > 0.5 + + # Update counts based on predictions + if true_positive and pred_positive: + true_positives += 1 + elif not true_positive and not pred_positive: + true_negatives += 1 + elif not true_positive and pred_positive: + false_positives += 1 + else: + false_negatives += 1 + + predictions.append({ + "text": text, + "true": "positive" if true_positive else "negative", + "predicted": "positive" if pred_positive else "negative", + "scores": pred_cats + }) + + metrics = calculate_metrics(true_positives, true_negatives, false_positives, false_negatives) + return metrics, predictions + + +def main(): + try: + print("Loading spaCy model...") + nlp = spacy.load("en_core_web_lg") + except OSError: + print("Downloading spaCy model...") + spacy.cli.download("en_core_web_lg") + nlp = spacy.load("en_core_web_lg") + + print("Adding custom text categorizer...") + config = { + "learning_rate": 0.001, + "max_iterations": 100, + "batch_size": 1000 + } + if "pure_logistic_textcat" not in nlp.pipe_names: + textcat = nlp.add_pipe("pure_logistic_textcat", config=config) + textcat.labels = {"positive", "negative"} + + print("Preparing training examples...") + train_examples = [] + for text, annotations in TRAIN_DATA: + doc = nlp.make_doc(text) + example = Example.from_dict(doc, annotations) + train_examples.append(example) + + print("Training the model...") + textcat = nlp.get_pipe("pure_logistic_textcat") + losses = textcat.update(train_examples) + print(f"Training losses: {losses}") + + print("\nEvaluating the model...") + metrics, predictions = evaluate_model(nlp, TEST_DATA) + + print("\nEvaluation Metrics:") + print(f"Accuracy: {metrics['accuracy']:.3f}") + print(f"Precision: {metrics['precision']:.3f}") + print(f"Recall: {metrics['recall']:.3f}") + print(f"F1 Score: {metrics['f1']:.3f}") + + print("\nDetailed Predictions:") + for pred in predictions: + print(f"\nText: {pred['text']}") + print(f"True label: {pred['true']}") + print(f"Predicted: {pred['predicted']}") + print(f"Positive score: {pred['scores']['positive']:.3f}") + print(f"Negative score: {pred['scores']['negative']:.3f}") + +if __name__ == "__main__": + main() diff --git a/spacy/pipeline/logreg/myenv/Scripts/Activate.ps1 b/spacy/pipeline/logreg/myenv/Scripts/Activate.ps1 new file mode 100644 index 000000000..d00d7d4fb --- /dev/null +++ b/spacy/pipeline/logreg/myenv/Scripts/Activate.ps1 @@ -0,0 +1,443 @@ +<# +.Synopsis +Activate a Python virtual environment for the current PowerShell session. + +.Description +Pushes the python executable for a virtual environment to the front of the +$Env:PATH environment variable and sets the prompt to signify that you are +in a Python virtual environment. Makes use of the command line switches as +well as the `pyvenv.cfg` file values present in the virtual environment. + +.Parameter VenvDir +Path to the directory that contains the virtual environment to activate. The +default value for this is the parent of the directory that the Activate.ps1 +script is located within. + +.Parameter Prompt +The prompt prefix to display when this virtual environment is activated. By +default, this prompt is the name of the virtual environment folder (VenvDir) +surrounded by parentheses and followed by a single space (ie. '(.venv) '). + +.Example +Activate.ps1 +Activates the Python virtual environment that contains the Activate.ps1 script. + +.Example +Activate.ps1 -Verbose +Activates the Python virtual environment that contains the Activate.ps1 script, +and shows extra information about the activation as it executes. + +.Example +Activate.ps1 -VenvDir C:\Users\MyUser\Common\.venv +Activates the Python virtual environment located in the specified location. + +.Example +Activate.ps1 -Prompt "MyPython" +Activates the Python virtual environment that contains the Activate.ps1 script, +and prefixes the current prompt with the specified string (surrounded in +parentheses) while the virtual environment is active. + +.Notes +On Windows, it may be required to enable this Activate.ps1 script by setting the +execution policy for the user. You can do this by issuing the following PowerShell +command: + +PS C:\> Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser + +For more information on Execution Policies: +https://go.microsoft.com/fwlink/?LinkID=135170 + +#> +Param( + [Parameter(Mandatory = $false)] + [String] + $VenvDir, + [Parameter(Mandatory = $false)] + [String] + $Prompt +) + +<# Function declarations --------------------------------------------------- #> + +<# +.Synopsis +Remove all shell session elements added by the Activate script, including the +addition of the virtual environment's Python executable from the beginning of +the PATH variable. + +.Parameter NonDestructive +If present, do not remove this function from the global namespace for the +session. + +#> +function global:deactivate ([switch]$NonDestructive) { + # Revert to original values + + # The prior prompt: + if (Test-Path -Path Function:_OLD_VIRTUAL_PROMPT) { + Copy-Item -Path Function:_OLD_VIRTUAL_PROMPT -Destination Function:prompt + Remove-Item -Path Function:_OLD_VIRTUAL_PROMPT + } + + # The prior PYTHONHOME: + if (Test-Path -Path Env:_OLD_VIRTUAL_PYTHONHOME) { + Copy-Item -Path Env:_OLD_VIRTUAL_PYTHONHOME -Destination Env:PYTHONHOME + Remove-Item -Path Env:_OLD_VIRTUAL_PYTHONHOME + } + + # The prior PATH: + if (Test-Path -Path Env:_OLD_VIRTUAL_PATH) { + Copy-Item -Path Env:_OLD_VIRTUAL_PATH -Destination Env:PATH + Remove-Item -Path Env:_OLD_VIRTUAL_PATH + } + + # Just remove the VIRTUAL_ENV altogether: + if (Test-Path -Path Env:VIRTUAL_ENV) { + Remove-Item -Path env:VIRTUAL_ENV + } + + # Just remove VIRTUAL_ENV_PROMPT altogether. + if (Test-Path -Path Env:VIRTUAL_ENV_PROMPT) { + Remove-Item -Path env:VIRTUAL_ENV_PROMPT + } + + # Just remove the _PYTHON_VENV_PROMPT_PREFIX altogether: + if (Get-Variable -Name "_PYTHON_VENV_PROMPT_PREFIX" -ErrorAction SilentlyContinue) { + Remove-Variable -Name _PYTHON_VENV_PROMPT_PREFIX -Scope Global -Force + } + + # Leave deactivate function in the global namespace if requested: + if (-not $NonDestructive) { + Remove-Item -Path function:deactivate + } +} + +<# +.Description +Get-PyVenvConfig parses the values from the pyvenv.cfg file located in the +given folder, and returns them in a map. + +For each line in the pyvenv.cfg file, if that line can be parsed into exactly +two strings separated by `=` (with any amount of whitespace surrounding the =) +then it is considered a `key = value` line. The left hand string is the key, +the right hand is the value. + +If the value starts with a `'` or a `"` then the first and last character is +stripped from the value before being captured. + +.Parameter ConfigDir +Path to the directory that contains the `pyvenv.cfg` file. +#> +function Get-PyVenvConfig( + [String] + $ConfigDir +) { + Write-Verbose "Given ConfigDir=$ConfigDir, obtain values in pyvenv.cfg" + + # Ensure the file exists, and issue a warning if it doesn't (but still allow the function to continue). + $pyvenvConfigPath = Join-Path -Resolve -Path $ConfigDir -ChildPath 'pyvenv.cfg' -ErrorAction Continue + + # An empty map will be returned if no config file is found. + $pyvenvConfig = @{ } + + if ($pyvenvConfigPath) { + + Write-Verbose "File exists, parse `key = value` lines" + $pyvenvConfigContent = Get-Content -Path $pyvenvConfigPath + + $pyvenvConfigContent | ForEach-Object { + $keyval = $PSItem -split "\s*=\s*", 2 + if ($keyval[0] -and $keyval[1]) { + $val = $keyval[1] + + # Remove extraneous quotations around a string value. + if ("'""".Contains($val.Substring(0, 1))) { + $val = $val.Substring(1, $val.Length - 2) + } + + $pyvenvConfig[$keyval[0]] = $val + Write-Verbose "Adding Key: '$($keyval[0])'='$val'" + } + } + } + return $pyvenvConfig +} + + +<# Begin Activate script --------------------------------------------------- #> + +# Determine the containing directory of this script +$VenvExecPath = Split-Path -Parent $MyInvocation.MyCommand.Definition +$VenvExecDir = Get-Item -Path $VenvExecPath + +Write-Verbose "Activation script is located in path: '$VenvExecPath'" +Write-Verbose "VenvExecDir Fullname: '$($VenvExecDir.FullName)" +Write-Verbose "VenvExecDir Name: '$($VenvExecDir.Name)" + +# Set values required in priority: CmdLine, ConfigFile, Default +# First, get the location of the virtual environment, it might not be +# VenvExecDir if specified on the command line. +if ($VenvDir) { + Write-Verbose "VenvDir given as parameter, using '$VenvDir' to determine values" +} +else { + Write-Verbose "VenvDir not given as a parameter, using parent directory name as VenvDir." + $VenvDir = $VenvExecDir.Parent.FullName.TrimEnd("\\/") + Write-Verbose "VenvDir=$VenvDir" +} + +# Next, read the `pyvenv.cfg` file to determine any required value such +# as `prompt`. +$pyvenvCfg = Get-PyVenvConfig -ConfigDir $VenvDir + +# Next, set the prompt from the command line, or the config file, or +# just use the name of the virtual environment folder. +if ($Prompt) { + Write-Verbose "Prompt specified as argument, using '$Prompt'" +} +else { + Write-Verbose "Prompt not specified as argument to script, checking pyvenv.cfg value" + if ($pyvenvCfg -and $pyvenvCfg['prompt']) { + Write-Verbose " Setting based on value in pyvenv.cfg='$($pyvenvCfg['prompt'])'" + $Prompt = $pyvenvCfg['prompt']; + } + else { + Write-Verbose " Setting prompt based on parent's directory's name. 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zsh, which have a hash command that must + # be called to get it to forget past commands. Without forgetting + # past commands the $PATH changes we made may not be respected + if [ -n "${BASH:-}" -o -n "${ZSH_VERSION:-}" ] ; then + hash -r 2> /dev/null + fi + + if [ -n "${_OLD_VIRTUAL_PS1:-}" ] ; then + PS1="${_OLD_VIRTUAL_PS1:-}" + export PS1 + unset _OLD_VIRTUAL_PS1 + fi + + unset VIRTUAL_ENV + unset VIRTUAL_ENV_PROMPT + if [ ! "${1:-}" = "nondestructive" ] ; then + # Self destruct! + unset -f deactivate + fi +} + +# unset irrelevant variables +deactivate nondestructive + +VIRTUAL_ENV="C:\Users\samhi\spaCy\spacy\pipeline\logreg\myenv" +export VIRTUAL_ENV + +_OLD_VIRTUAL_PATH="$PATH" +PATH="$VIRTUAL_ENV/Scripts:$PATH" +export PATH + +# unset PYTHONHOME if set +# this will fail if PYTHONHOME is set to the empty string (which is bad anyway) +# could use `if (set -u; : $PYTHONHOME) ;` in bash +if [ -n "${PYTHONHOME:-}" ] ; then + _OLD_VIRTUAL_PYTHONHOME="${PYTHONHOME:-}" + unset PYTHONHOME +fi + +if [ -z "${VIRTUAL_ENV_DISABLE_PROMPT:-}" ] ; then + _OLD_VIRTUAL_PS1="${PS1:-}" + PS1="(myenv) ${PS1:-}" + export PS1 + VIRTUAL_ENV_PROMPT="(myenv) " + export VIRTUAL_ENV_PROMPT +fi + +# This should detect bash and zsh, which have a hash command that must +# be called to get it to forget past commands. Without forgetting +# past commands the $PATH changes we made may not be respected +if [ -n "${BASH:-}" -o -n "${ZSH_VERSION:-}" ] ; then + hash -r 2> /dev/null +fi diff --git a/spacy/pipeline/logreg/myenv/Scripts/f2py.exe b/spacy/pipeline/logreg/myenv/Scripts/f2py.exe new file mode 100644 index 0000000000000000000000000000000000000000..48e9d7f53c750ba4d80189ea3741f6d42f46a767 GIT binary patch literal 108421 zcmeFadw5jU)%ZWjWXKQ_P7p@IO-Bic#!G0tBo5RJ%;*`JC{}2xf}+8Qib}(bU_}i* zNt@v~ed)#4zP;$%+PC)dzP-K@u*HN(5-vi(8(ykWyqs}B0W}HN^ZTrQW|Da6`@GNh z?;nrOIeVXdS$plZ*IsMwwRUQ*Tjz4ST&_I+w{4fJg{S
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