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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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Co-occurring Patterns of Mittens

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Dr. Rishabh Pathak

Mittens in EEG recordings are often associated with several co-occurring patterns, particularly during non-rapid eye movement (NREM) sleep. These patterns include:

1. Sleep Spindles

    • Sleep spindles are bursts of oscillatory brain activity that typically occur in NREM sleep. They are characterized by a frequency of 12-16 Hz and can be seen alongside mittens, contributing to the overall electrographic features of sleep.

2. K Complexes

    • K complexes are large, biphasic waves that occur in NREM sleep and are often considered a marker of sleep stability. They can appear in conjunction with mittens, although they differ in waveform characteristics.

3. Positive Occipital Sharp Transients of Sleep (POSTS)

    • POSTS are transient waveforms that occur in the occipital region during sleep. They are typically positive and can co-occur with mittens, adding to the complexity of the EEG during deep sleep.

4. Generalized Delta Frequency Range Activity

    • Mittens are often accompanied by prominent delta activity, particularly in the deeper stages of NREM sleep. This delta activity is characterized by slower frequency waves and is a common background feature during sleep.

5. Anterior Rhythmic Activity

    • EEGs that include mittens may also show bursts of anterior rhythmic activity, which can be indicative of the brain's transition between different sleep stages or arousal states.

Summary

The co-occurring patterns of mittens highlight their presence within the broader context of NREM sleep, where they interact with various other sleep-related EEG features. Recognizing these associated patterns is important for accurate EEG interpretation and understanding the normal variations in sleep architecture.

 

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