Update README example

README.md

@@ -120,17 +120,16 @@ You may run:
 ```python
 print(model)
 ```
-to print the learned equations, which for the above should be close to:
+to print the learned equations:
 ```python
 PySRRegressor.equations = [
    pick      score                                           Equation           MSE  Complexity
-0         0.000000                                           3.598587  3.044337e+01           1
-1         1.074135                                          (x0 * x0)  3.552313e+00           3
-2         0.023611                          (-0.40477127 + (x0 * x0))  3.388464e+00           5
-3         0.855682                              ((x0 * x0) + cos(x3))  1.440074e+00           6
-4         0.876831                ((x0 * x0) + (2.5026207 * cos(x3)))  2.493328e-01           8
-5  >>>>  10.687394  ((-0.5000114 + (x0 * x0)) + (2.5382013 * cos(x...  1.299652e-10          10
-6         2.573098  ((-0.50000024 + (x0 * x0)) + (2.5382 * sin(1.5...  7.565937e-13          12
+0         0.000000                                          3.5082064  2.710828e+01           1
+1         0.964260                                          (x0 * x0)  3.940544e+00           3
+2         0.030096                          (-0.47978288 + (x0 * x0))  3.710349e+00           5
+3         0.840770                              ((x0 * x0) + cos(x3))  1.600564e+00           6
+4         0.928380                ((x0 * x0) + (2.5313091 * cos(x3)))  2.499724e-01           8
+5  >>>>  13.956461  ((-0.49999997 + (x0 * x0)) + (2.5382001 * cos(...  1.885665e-13          10
 ]
 ```
 This arrow in the `pick` column indicates which equation is currently selected by your
@@ -142,12 +141,10 @@ This arrow in the `pick` column indicates which equation is currently selected b
 SymPy format (`sympy_format`), and even JAX and PyTorch format 
 (both of which are differentiable).
 
-
-### Notes
-
-- `score` - a metric akin to Occam's razor; you should use this to help select the "true" equation.
-- `sympy_format` - sympy equation.
-- `lambda_format` - a lambda function for that equation, that you can pass values through.
+There are several other useful features such as denoising (e.g., `denoising=True`),
+feature selection (e.g., `select_k_features=3`).
+For a summary of features and options, see [this docs page](https://pysr.readthedocs.io/en/latest/docs/options/).
+You can see the full API at [this page](https://pysr.readthedocs.io/en/latest/docs/api-documentation/).
 
 
 # Docker