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4 changes: 2 additions & 2 deletions unit04_model_sel/lab_neural_partial.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -192,11 +192,11 @@
"\n",
"One way we can improve the model accuracy is to used delayed version of the features. Specifically, the model we used above mapped the features \n",
"\n",
" yhat[i,k] = \\sum_{j=0}^{p-1} X[i,j]*w[j,k] + b[k]\n",
" $yhat[i,k] = \\sum_{j=0}^{p-1} X[i,j]*w[j,k] + b[k]$\n",
" \n",
"where `p` is the number of features and `w[j,k]` is a matrix of coefficients. In this model, `yhat[i,:]` at time `i` was only dependent on the inputs `X[i,:]` at time `i`. In signal processing, this is called a *memoryless* model. However, in many physical systems, such as those that arise in neuroscience, there is a delay between the inputs `X[i,:]` and the outputs `y[i]`. For such cases, we can use a model of the form,\n",
"\n",
" yhat[i+d,k] = \\sum_{k=0}^d \\sum_{j=0}^{p-1} \\sum_{m=0}^d X[i+m,j]*W[j,m,k] + b[k]\n",
" $yhat[i+d,k] = \\sum_{k=0}^d \\sum_{j=0}^{p-1} \\sum_{m=0}^d X[i+m,j]*W[j,m,k] + b[k]$\n",
" \n",
"where `W` is a 3-dim array of coefficients where:\n",
"\n",
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