Yes, it is true, no Machine Learning (ML) model may produce 100% accurate results, even not the Human brain. During the data analysis, we need some approximations, w.r.t models as well as Data at hand. All such approximations may produce some errors. For you knowledge, I would like to read the following attached book.

Yes, a predictive model with 100% accuracy is possible. But only in the ideal world. The first time I was training a model on a dataset, I got an accuracy of 100% . I was all happy and merry about it. But then, when I actually tested this model against the test dataset (the dataset that wasnt used during training), the accuracy decreased from 100% to 35%. The reason: OVERFITTING. In Machine Learning , it is always good to have a model that performs well on both the training set as well as the test set . Which essentially translates to the model learning enough features about the dataset to make a generalized decision, given the inputs.

https://www.quora.com/Is-it-possible-to-get-a-predictive-model-with-100-accuracy-ever

Predictive analytics is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal is to go beyond knowing what has happened to providing a best assessment of what will happen in the future.

When it comes to machine learning, my machine learning adviser constantly stressed that there are two things to be concerned about. The first is to be Overfitting and Underfitting With Machine Learning Algorithms. The second is the accuracy of more than 95% or 90%. I do not expect 100% accuracy.

Dear Hayes Anyasodor

The result depends on all the methods that are carried out, the type of data and the amount of data. You can review this paper on the influence of preprocessing, segmentation and optimization in the case of convolutional networks applied to a medical imaging case study.

Chapter Accurate Identification of Tomograms of Lung Nodules Using C...

Kind Regards,

Cecilia-Irene Loeza-Mejía