alkzar90 commited on
Commit
e9098e7
·
1 Parent(s): 9e06d30
Files changed (1) hide show
  1. app.py +1 -1
app.py CHANGED
@@ -22,7 +22,7 @@ cost_function = st.sidebar.radio('What cost function you want to use for the fit
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  # Generate random data
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  X = np.column_stack((jnp.ones(number_of_observations),
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- jax.random.uniform(key, shape=(number_of_observations,), minval=0., maxval=1.))
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  w = jnp.array([3.0, -20.0, 32.0]) # coefficients
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  X = jnp.column_stack((X, X[:,1] ** 2)) # add x**2 column
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  additional_noise = 8 * jax.random.bernoulli(key, p=0.08, shape=[number_of_observations,])
 
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  # Generate random data
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  X = np.column_stack((jnp.ones(number_of_observations),
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+ jax.random.uniform(key, shape=(number_of_observations,), minval=0., maxval=1.)))
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  w = jnp.array([3.0, -20.0, 32.0]) # coefficients
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  X = jnp.column_stack((X, X[:,1] ** 2)) # add x**2 column
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  additional_noise = 8 * jax.random.bernoulli(key, p=0.08, shape=[number_of_observations,])