predict_single_ch: Leave one out classification of a single trial
In nateaff/eeg-complex: Analyses for "Complexity-based seizure prediction"
Description
Usage
Arguments
Value
Description
Takes the mean of features on segmented data and
predicts segments using random forest classifier
Usage
1
predict_single_ch(df_, data_, tnum, train, colnums, thresh = 0.45)
Arguments
data_
: Segment book-keeping data
df:
Features means for a given trial
tindex
: The trial index (refers to the filtered index)
colnums:
df_means columns to use in classification
Value
A list of 1. Prediction probability vector,
2. Prediction vector
3. Weight vector
nateaff/eeg-complex documentation built on May 14, 2019, 2:55 p.m.
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Description Usage Arguments Value
Description
Takes the mean of features on segmented data and predicts segments using random forest classifier
Usage
1 | predict_single_ch(df_, data_, tnum, train, colnums, thresh = 0.45)
|
Arguments
data_ |
: Segment book-keeping data |
df: |
Features means for a given trial |
tindex |
: The trial index (refers to the filtered index) |
colnums: |
df_means columns to use in classification |
Value
A list of 1. Prediction probability vector, 2. Prediction vector 3. Weight vector
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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