1
상호 배타적이지 않은 카테고리를 분류 할 수있는 딥 러닝 모델
예 : 직업 설명에 "영국의 Java Senior Engineer"문장이 있습니다. 나는 2 개 종류로 예측하는 깊은 학습 모델을 사용하려면 : English 와 IT jobs. 기존 분류 모델을 사용하는 경우 softmax마지막 레이어에서 함수가있는 레이블 하나만 예측할 수 있습니다 . 따라서 두 모델 신경망을 사용하여 두 범주 모두에서 "예"/ "아니오"를 예측할 수 있지만 …
9
machine-learning
deep-learning
natural-language
tensorflow
sampling
distance
non-independent
application
regression
machine-learning
logistic
mixed-model
control-group
crossover
r
multivariate-analysis
ecology
procrustes-analysis
vegan
regression
hypothesis-testing
interpretation
chi-squared
bootstrap
r
bioinformatics
bayesian
exponential
beta-distribution
bernoulli-distribution
conjugate-prior
distributions
bayesian
prior
beta-distribution
covariance
naive-bayes
smoothing
laplace-smoothing
distributions
data-visualization
regression
probit
penalized
estimation
unbiased-estimator
fisher-information
unbalanced-classes
bayesian
model-selection
aic
multiple-regression
cross-validation
regression-coefficients
nonlinear-regression
standardization
naive-bayes
trend
machine-learning
clustering
unsupervised-learning
wilcoxon-mann-whitney
z-score
econometrics
generalized-moments
method-of-moments
machine-learning
conv-neural-network
image-processing
ocr
machine-learning
neural-networks
conv-neural-network
tensorflow
r
logistic
scoring-rules
probability
self-study
pdf
cdf
classification
svm
resampling
forecasting
rms
volatility-forecasting
diebold-mariano
neural-networks
prediction-interval
uncertainty