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Uncertainty in Multiclass Classification

Dr. Rishabh Pathak
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 ...
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Lambda Waves Compared to the Positive Occipital Sharp Transients of Sleep

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Dr. Rishabh Pathak

Lambda waves and Positive Occipital Sharp Transients of Sleep (POSTS) are both EEG patterns observed in the occipital region, but they have distinct characteristics and contexts of occurrence. Here are the key differences between the two:

1. State of Occurrence

    • Lambda Waves: These waves occur exclusively during wakefulness, particularly when the eyes are open and the individual is engaged in visual exploration. They are associated with visual attention and processing.
    • POSTS: In contrast, POSTS occur only during non-rapid eye movement (NREM) sleep. They are not present during wakefulness and are typically observed in a sleep state.

2. Waveform Characteristics

    • Lambda Waves: Lambda waves are characterized by a triangular or sawtooth waveform, with a sharp contour at the apex. They are generally diphasic or sometimes triphasic.
    • POSTS: Positive Occipital Sharp Transients of Sleep have a different morphology and are typically seen as sharp, positive waves that can occur in trains. They do not exhibit the triangular shape characteristic of lambda waves.

3. Temporal Patterns

    • Lambda Waves: These waves are often isolated transients that may recur at intervals of 200 to 500 milliseconds. They are not typically seen in trains.
    • POSTS: POSTS frequently occur in trains, which is a common feature of this pattern during sleep. This repetitive nature distinguishes them from the more sporadic lambda waves.

4. Response to Eye Closure

    • Lambda Waves: The presence of lambda waves is blocked when the eyes are closed, as they are dependent on visual stimuli and eye movements. They are absent during sustained eye closure.
    • POSTS: Conversely, POSTS are not affected by eye closure and can be present regardless of whether the eyes are open or closed, as they occur during sleep.

5. Clinical Implications

    • Lambda Waves: While generally considered a normal finding in awake individuals, abnormal patterns or asymmetry in lambda waves may indicate underlying neurological issues related to visual processing.
    • POSTS: POSTS are also considered a normal finding during sleep, but their presence can be indicative of the sleep state and may vary with different sleep stages.

Conclusion

In summary, lambda waves and Positive Occipital Sharp Transients of Sleep are distinct EEG patterns that differ in their state of occurrence, waveform characteristics, temporal patterns, and response to eye closure. Understanding these differences is crucial for accurate interpretation of EEG recordings and for distinguishing between normal and abnormal brain activity.

 

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