You will be shown an excerpt from a computer science scientific research paper, followed by a question about the paper. Please answer the question. Do not include any text in your response other than the answer.

Context: In this section, we describe the tasks used for our analysis, which we refer to as NILM (measuring Non-linguistic Inductive bias in Language Models). The tasks correspond to three task paradigms: (1) quantitative computation, (2) regular expressions, and (3) string reasoning. Each task in NILM is posed as a classification task. The descriptions for all the tasks with input and output examples, class labels and the input range are shown in Table 1. Each task has a synthetically generated dataset with train/dev/test splits222The training set size for all tasks is 10K, dev set size is 1K and test set size is 1K, except for tasks on recognizing regular expressions, where the test set size is 2K following previous work Bhattamishra et al. (2020).. To avoid biases in the datasets, relevant numbers and strings in individual examples are uniformly sampled from the appropriate ranges. 

Question: Is this true? NILM has only classification tasks.
It's true, becase NILM has three kinds of tasks, and all tasks it classification task.