| @@ -139,7 +139,7 @@ Out: | |||||
| First true equation with length 5 in the training dataset: | First true equation with length 5 in the training dataset: | ||||
| .. image:: ../img/hed_dataset1.png | |||||
| .. image:: ../_static/img/hed_dataset1.png | |||||
| :width: 300px | :width: 300px | ||||
| .. code:: none | .. code:: none | ||||
| @@ -147,7 +147,7 @@ Out: | |||||
| First true equation with length 8 in the training dataset: | First true equation with length 8 in the training dataset: | ||||
| .. image:: ../img/hed_dataset2.png | |||||
| .. image:: ../_static/img/hed_dataset2.png | |||||
| :width: 480px | :width: 480px | ||||
| .. code:: none | .. code:: none | ||||
| @@ -155,7 +155,7 @@ Out: | |||||
| First false equation with length 5 in the training dataset: | First false equation with length 5 in the training dataset: | ||||
| .. image:: ../img/hed_dataset3.png | |||||
| .. image:: ../_static/img/hed_dataset3.png | |||||
| :width: 300px | :width: 300px | ||||
| .. code:: none | .. code:: none | ||||
| @@ -163,7 +163,7 @@ Out: | |||||
| First false equation with length 8 in the training dataset: | First false equation with length 8 in the training dataset: | ||||
| .. image:: ../img/hed_dataset4.png | |||||
| .. image:: ../_static/img/hed_dataset4.png | |||||
| :width: 480px | :width: 480px | ||||
| @@ -131,7 +131,7 @@ Out: | |||||
| X in the 1001st data example (a list of images): | X in the 1001st data example (a list of images): | ||||
| .. image:: ../img/hwf_dataset1.png | |||||
| .. image:: ../_static/img/hwf_dataset1.png | |||||
| :width: 210px | :width: 210px | ||||
| .. code:: none | .. code:: none | ||||
| @@ -145,7 +145,7 @@ Out: | |||||
| X in the 3001st data example (a list of images): | X in the 3001st data example (a list of images): | ||||
| .. image:: ../img/hwf_dataset2.png | |||||
| .. image:: ../_static/img/hwf_dataset2.png | |||||
| :width: 350px | :width: 350px | ||||
| .. code:: none | .. code:: none | ||||
| @@ -124,7 +124,7 @@ Out: | |||||
| X in the first data example (a list of two images): | X in the first data example (a list of two images): | ||||
| .. image:: ../img/mnist_add_datasets.png | |||||
| .. image:: ../_static/img/mnist_add_datasets.png | |||||
| :width: 200px | :width: 200px | ||||
| @@ -18,7 +18,7 @@ The ABL-Package comprises three primary parts: **Data**, **Learning**, and | |||||
| **Reasoning**, corresponding to the three pivotal components of current | **Reasoning**, corresponding to the three pivotal components of current | ||||
| AI: data, models, and knowledge. Below is an overview of the ABL-Package. | AI: data, models, and knowledge. Below is an overview of the ABL-Package. | ||||
| .. image:: ../img/ABL-Package.png | |||||
| .. image:: ../_static/img/ABL-Package.png | |||||
| **Data** part manages the storage, operation, and evaluation of data efficiently. | **Data** part manages the storage, operation, and evaluation of data efficiently. | ||||
| It includes the ``ListData`` class, which defines the data structures used in | It includes the ``ListData`` class, which defines the data structures used in | ||||
| @@ -64,7 +64,7 @@ Subsequently, these pseudo-labels are processed to minimize inconsistencies with | |||||
| which in turn revise the outcomes of the learning model, and then | which in turn revise the outcomes of the learning model, and then | ||||
| fed back for further training ``ABLModel.train``. | fed back for further training ``ABLModel.train``. | ||||
| .. image:: ../img/usage.png | |||||
| .. image:: ../_static/img/usage.png | |||||
| To implement this process, the following five steps are necessary: | To implement this process, the following five steps are necessary: | ||||
| @@ -45,15 +45,15 @@ ABL-Package requires user data to be either structured as a tuple ``(X, gt_pseud | |||||
| As an illustration, in the MNIST Addition task, the data are organized as follows: | As an illustration, in the MNIST Addition task, the data are organized as follows: | ||||
| .. image:: ../img/Datasets_1.png | |||||
| .. image:: ../_static/img/Datasets_1.png | |||||
| :width: 350px | :width: 350px | ||||
| :align: center | :align: center | ||||
| .. |data_example| image:: ../img/data_example.png | |||||
| .. |data_example| image:: ../_static/img/data_example.png | |||||
| :alt: alternate text | :alt: alternate text | ||||
| :scale: 8% | :scale: 8% | ||||
| .. |instance| image:: ../img/instance.png | |||||
| .. |instance| image:: ../_static/img/instance.png | |||||
| :alt: alternate text | :alt: alternate text | ||||
| :scale: 55% | :scale: 55% | ||||
| @@ -8,7 +8,7 @@ Here, a set of data examples is given, including training instances | |||||
| These data are then used to train a classifier model :math:`f`, | These data are then used to train a classifier model :math:`f`, | ||||
| aiming to accurately predict the unseen data instances. | aiming to accurately predict the unseen data instances. | ||||
| .. image:: ../img/ML.png | |||||
| .. image:: ../_static/img/ML.png | |||||
| :align: center | :align: center | ||||
| :width: 280px | :width: 280px | ||||
| @@ -46,7 +46,7 @@ base. | |||||
| The following figure illustrates this process: | The following figure illustrates this process: | ||||
| .. image:: ../img/ABL.png | |||||
| .. image:: ../_static/img/ABL.png | |||||
| :width: 800px | :width: 800px | ||||
| We can observe that in the above figure, the left half involves machine | We can observe that in the above figure, the left half involves machine | ||||
| @@ -16,7 +16,7 @@ ABL-Package encapsulates advanced ABL techniques, providing users with | |||||
| an efficient and convenient package to develop dual-driven ABL systems | an efficient and convenient package to develop dual-driven ABL systems | ||||
| that leverage both data and knowledge. | that leverage both data and knowledge. | ||||
| .. image:: img/ABL.png | |||||
| .. image:: _static/img/ABL.png | |||||
| Installation | Installation | ||||
| ------------ | ------------ | ||||