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Uncertainty in Multiclass Classification

1. What is Uncertainty in Classification? Uncertainty refers to the model’s confidence or doubt in its predictions. Quantifying uncertainty is important to understand how reliable each prediction is. In multiclass classification , uncertainty estimates provide probabilities over multiple classes, reflecting how sure the model is about each possible class. 2. Methods to Estimate Uncertainty in Multiclass Classification Most multiclass classifiers provide methods such as: predict_proba: Returns a probability distribution across all classes. decision_function: Returns scores or margins for each class (sometimes called raw or uncalibrated confidence scores). The probability distribution from predict_proba captures the uncertainty by assigning a probability to each class. 3. Shape and Interpretation of predict_proba in Multiclass Output shape: (n_samples, n_classes) Each row corresponds to the probabilities of ...

Near Infrared Spectroscopy

Near Infrared Spectroscopy (NIRS) is a non-invasive optical imaging technique that measures changes in blood oxygenation levels in the brain by detecting near-infrared light absorption. 

1.     Principle:

    • Near Infrared Spectroscopy (NIRS) is based on the principle that near-infrared light can penetrate biological tissues, including the human skull, allowing for the measurement of changes in blood oxygen levels in the brain.
    • NIRS utilizes near-infrared light sources and detectors placed on the scalp to monitor changes in light absorption, which are indicative of variations in oxygenated and deoxygenated hemoglobin concentrations in the brain.

2.     Applications:

    • NIRS is commonly used in neuroscience research to study brain activity, cognitive functions, and hemodynamic responses during various tasks and stimuli.
    • NIRS has applications in studying cognitive processes, language processing, motor functions, emotional responses, and developmental changes in the brain, particularly in infants and young children.

3.     Advantages:

    • Non-Invasive: NIRS is a non-invasive imaging technique that does not require exposure to ionizing radiation, making it safe for use in various populations, including infants, children, and clinical populations.
    • Portable and Flexible: NIRS systems are portable and adaptable for use in different settings, such as laboratories, hospitals, and research facilities, allowing for flexible data collection and monitoring.

4.     Limitations:

    • Depth of Penetration: NIRS has limited depth penetration compared to other neuroimaging techniques like fMRI, restricting its ability to measure brain activity in deeper brain regions.
    • Signal Contamination: NIRS signals can be affected by scalp blood flow, motion artifacts, and signal contamination from superficial tissues, requiring careful data processing and artifact correction.

5.     Research and Clinical Use:

    • NIRS is used in cognitive neuroscience research to investigate brain function, neural correlates of behavior, and developmental changes in brain activity.
    • In clinical settings, NIRS is employed to study neurological disorders, brain injuries, stroke rehabilitation, and cognitive impairments, providing valuable insights into brain function and hemodynamic responses in patient populations.

In summary, Near Infrared Spectroscopy (NIRS) is a valuable non-invasive optical imaging technique used in neuroscience research and clinical settings to study brain activity, cognitive functions, and hemodynamic responses. NIRS offers advantages such as portability, safety, and flexibility, making it a versatile tool for investigating brain function and neural processes in various populations and experimental conditions.

 

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