The performance of a classification model where the prediction is a probability value between 0 and 1 is measured by logarithmic loss (or log loss). As the anticipated probability diverges from the actual label, log loss grows. For Kaggle contests, log loss is a popular measure.
The evaluation of performance is an important part of the machine learning process. It is, however, a difficult task. As a result, it must be carried out with caution if machine learning can be applied to radiation oncology or other fields with confidence.
Model assessment is the process of analysing a machine learning model's performance, as well as its strengths and weaknesses, using various evaluation criteria. Model evaluation is critical for determining a model's efficacy during the early stages of research, as well as for model monitoring.
The main types of evaluation are processes:
impact
outcome
summative
evaluation.
Learner's Ratings
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Reviews
S
Suresh Kumar
5
Hi Sir,
I want a clearity up on these
1. To learn Data Science "Machine learning" is part of it but we have to learn additionally python libraries (panda, numpy, matplotlib) or else in ML enough.
A
Ayush Bharti
4
how can i download the finaldata.csv?
J
Jagannath Mahato
5
Hello Kushal Sir!
Your way of teaching is very good. I thank you from my heart ❤️ that you are providing such good content for free.
M
Muhammad Qasim
5
Hi Kushal ! Your way of teaching is extremely helpful and you are one of the best teacher in the world.
Extremely helpful and I recommend to my peer as well for this course.
S
Shafi Akhtar
5
None
A
Aniket Kumar prasad
5
Very helpful and easy to understand all the concepts, best teacher for learning ML.
R
Rishu Shrivastav
5
explained everything in detail. I have a question learnvern provide dataset , and ppt ? or not?
V
VIKAS CHOUBEY
5
very nicely explained
V
Vrushali Kandesar
5
Awesome and very nicely explained!!!
One importing thing to notify to team is by mistakenly navie's practical has been added under svm lecture and vice versa (Learning Practical 1)
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