Message-ID: <1234624764.179.1632427506658.JavaMail.bigchem@cpu>
Subject: Exported From Confluence
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Model creatio=
n wizard
You can create a single model using web interface by accessing the "=
;Models > Create a model" menu as shown below, which will open a wi=
zard-like dialogue with a series of the necessary configuration steps.

First, you have to select a training and (optionally) a validation set. =
It is possible to have multiple validation sets. We assume that you have al=
ready prepared the sets=
.
On the same screen, it is required to select:
- the unit of measurement for the model
- the desired machine learning method
- the desired validation protocol (cross validation, bagging or no valida=
tion)

The next screen allows to configure the preprocessing of molecular struc=
tures. The options include:
- Standardization (e.g., of nitro-groups)
- Neutralisation of ions
- Removal of salts (by keeping the counter-ion)
- Cleaning of structures (by converting it to SMILES and back to SD-file)=

Molecular descriptor=
s
The next important step is the choice of molecular descriptors. OCHEM su=
pports more than 20 descriptor packages provided by different vendors.
OCHEM policy is to integrate state-of-the art descriptors rather than to d=
evelop own solutions.

On the next step, we have to configure filtering of descriptors. The mai=
n filtering options include:
- elimination of constant or semi-constant descriptors
- unsupervised forward selection
- extraction of PCAs
- manual selection of the desired descriptors from a list

Machine learning me=
thod
Next, we have to configure the machine learning method. This step is met=
hod-specific. The screenshot below shows the configuration options for a ne=
ural network model.
Naturally, the other machine learning methods (e.g=
., linear regression, PLS, random forest, etc) will have different options.=

Initiating the =
calculations
Now, we are ready to start calculations. In the dialog below, we have to=
give our model a name, define the priority of this task and, finally, init=
iate the calculations.
We recommend using high and extra-high prioriti=
es only for fast tasks (e.g., models with less than 300-500 molecules in th=
e training set).

The next screen shows the progress of calculations. It is possible to fe=
tch results later (in one hour, one day or more) from the registry of pendi=
ng tasks.

The registry of pending tasks displays the status of all currently runni=
ng calculation tasks. Once the task is ready, it will become "green&qu=
ot;, and it will be possible to fetch it by clicking a green checkbox=
icon on the right.


After you fetch the calculation task you will be presented with a model =
profile.
The model profile displays basic model statistics (RMSE, R2, etc), scatt=
er plot, applicability domain plots, etc. On this step, you can either save=
your model or discard it in case if the model performance is unsatisfactor=
y.

Accessing your model=
h2>
After you save your model, it will become available from the browser of =
models:

The browser of models displays all the publicly available models d=
eveloped by other OCHEM users as well as your own private models. Here, it =
is possible to search for models by various criteria.
The displayed in=
formation includes:
- model name
- training and validation sets
- machine learning method
Each available model has a model profile described above, which contains=
the detailed statistics, the scatter plots and confusion matrices for the =
classification models.

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